Add LLM-based patent classification tagging by technology domain

- Add classify_patent_tags() to LLMAnalyzer with canonical tag list
  (ai, semiconductors, materials, biotech, networking, other)
- Add patent_tags TEXT[] column to patents table with GIN index
- Run classification automatically in the analysis pipeline after
  patent processing; persist tags via update_patent_tags()
- Include tags in CompanyAnalysisResult and API response models
- Add ?tags= filter to GET /analyze/batch endpoint
- Add GET /analytics/tags endpoint for tag distribution data
- Add tag filter controls and distribution chart to Analytics page
- Add 12 unit tests covering classification, DB storage, and caching

Closes leeworks-agents/SPARC#1672

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

ROADMAP.md

@@ -7,86 +7,124 @@ Semiconductor Patent & Analytics Report Core -- development priorities.
 SPARC is a patent analysis platform with a working end-to-end pipeline:
 Python/FastAPI backend, React/TypeScript frontend, PostgreSQL for persistence
 and caching, Docker Compose for local development, and Gitea Actions CI/CD for
-image builds. Core features (patent retrieval via SerpAPI, PDF parsing, LLM
-analysis via OpenRouter/Claude, batch processing, JWT authentication, analytics
-dashboard) are all implemented and functional.
+image builds and testing. Core features include patent retrieval via SerpAPI,
+PDF parsing, LLM analysis via OpenRouter (multi-model: Claude, GPT-4o, Gemini,
+Llama), batch processing, JWT authentication, analytics dashboard with patent
+trend charts, scheduled recurring analysis with alerting, webhook notifications
+(Slack/Discord), CSV and PDF export, S3/MinIO storage, side-by-side company
+comparison, and dark mode.
+
+---
+
+## Completed
+
+Items that have been implemented and merged into main.
+
+### Security hardening
+
+- ~~Rotate default JWT secret.~~ Startup check refuses to start with the
+  default secret in non-development environments.
+- ~~CORS allow-origins are hardcoded.~~ Allowed origins are now configurable
+  via environment variable.
+- ~~Database credentials in docker-compose.yml.~~ Compose references `.env`
+  for sensitive values.
+
+### Error handling and resilience
+
+- ~~`get_db_client()` creates a new `DatabaseClient` on every call.~~ Refactored
+  to a shared pooled singleton initialized at startup.
+- ~~No rate limiting on auth endpoints.~~ Rate limiting middleware added to
+  `/auth/login` and `/auth/register`.
+
+### Test coverage
+
+- ~~API tests bypass authentication.~~ JWT auth integration tests added (33
+  cases covering registration, login, protected routes, token refresh, and
+  admin-only endpoints).
+- ~~No test stage in CI.~~ Gitea Actions workflow now runs `pytest` and gates
+  the build.
+- ~~No linting or type checking in CI.~~ `ruff` (Python) and `tsc --noEmit`
+  (TypeScript) added to CI pipeline.
+
+### Backend
+
+- ~~Add structured logging.~~ Python `logging` module used throughout.
+- ~~Make LLM model configurable.~~ `MODEL` environment variable accepted;
+  multi-model support with per-analysis selection (GPT-4o, Gemini, Claude,
+  Llama).
+- ~~SERP cache TTL hardcoded.~~ `SERP_CACHE_TTL_HOURS` exposed as env var.
+- ~~Patent PDF storage.~~ S3/MinIO object storage backend added alongside
+  local filesystem. Volume mount requirement documented.
+- ~~`analyze_single_patent` assumes local file.~~ Auto-download from cached
+  metadata link integrated.
+- ~~`Patent.patent_id` typed as `int`.~~ Fixed to `str`.
+
+### Frontend
+
+- ~~No loading/error states.~~ Skeleton loaders and error states added to
+  Batch and Analytics pages.
+- ~~No dark mode.~~ Full dark mode support with theme-aware chart colors.
+- ~~Missing lockfile.~~ `package-lock.json` committed.
+
+### Features (formerly P3)
+
+- ~~Export analysis reports.~~ CSV and PDF export endpoints implemented.
+- ~~Comparison view.~~ Side-by-side company patent portfolio comparison added.
+- ~~Scheduled/recurring analysis.~~ APScheduler-based periodic re-analysis
+  with configurable interval and change-threshold alerting.
+- ~~Webhook/notification support.~~ Slack, Discord, and generic HTTP POST
+  webhooks with retry logic.
+- ~~Multi-model support.~~ Model picker in Analysis and Batch pages; backend
+  allow-list validation.
+- ~~Patent trend charts.~~ Filing frequency and category distribution
+  visualizations added to Analytics page.
+- ~~OpenAPI client generation.~~ TypeScript API client auto-generated from
+  FastAPI spec with CI freshness check.
+
+### Resilience
+
+- ~~`_jobs` dict is in-memory only.~~ Database-backed job persistence
+  implemented using `db.list_jobs()` and `mark_stale_jobs_failed()`. The
+  in-memory `_jobs` dict has been removed.
+
+### Test coverage (P1/P2)
+
+- ~~Export endpoint tests.~~ Tests added for CSV and PDF export endpoints.
+- ~~Tracked company admin endpoint tests.~~ Tests added for `/admin/tracked`
+  CRUD endpoints and scheduler integration.
+- ~~Webhook integration tests.~~ Tests added for retry logic, Slack/Discord
+  payload format, and multi-URL dispatch.
+- ~~S3/MinIO storage backend tests.~~ Unit tests added for the S3 backend
+  (read, write, exists, delete, error handling).
+- ~~`analyze_single_patent` auto-download path tests.~~ Tests added for the
+  auto-download fallback (cache lookup, PDF download, FileNotFoundError).
+
+### Code quality
+
+- ~~Scheduler creates its own DatabaseClient.~~ Refactored to use the
+  application-level pooled `get_db_client()`.
 
 ---
 
 ## P1 -- High Priority
 
-These items address correctness, security, and reliability gaps that should be
-resolved before broader production use.
-
-### Security hardening
-
-- **Rotate default JWT secret.** `auth.py` ships a fallback
-  `sparc-secret-key-change-in-production` that will be used if `JWT_SECRET` is
-  unset. Add a startup check that refuses to start with the default secret in
-  non-development environments.
-- **CORS allow-origins are hardcoded.** `api.py` only permits
-  `localhost:3000` and `localhost:5173`. Make the allowed origins configurable
-  via environment variable so the dashboard works when deployed behind a real
-  domain.
-- **Database credentials in docker-compose.yml.** The compose file embeds
-  `postgres:postgres` in plain text. Reference a `.env` file or Docker secrets
-  instead.
-
-### Error handling and resilience
-
-- **`get_db_client()` in `auth.py` creates a new `DatabaseClient` on every
-  call.** This bypasses the connection pool and can exhaust database
-  connections under load. Refactor to share a single pooled client.
-- **`_jobs` dict is in-memory only.** Job state is lost on API restart. Persist
-  job status in PostgreSQL or Redis so async batch results survive restarts.
-- **No rate limiting on auth endpoints.** `/auth/login` and `/auth/register`
-  are unprotected against brute-force or abuse. Add rate limiting middleware.
-
-### Test coverage for auth and admin
-
-- The existing API tests (`tests/test_api.py`) bypass authentication entirely.
-  Add tests that exercise the JWT flow: registration, login, protected-route
-  access, token refresh, and admin-only endpoints.
+No outstanding P1 items. All previously listed items have been completed and
+moved to the Completed section above.
 
 ---
 
 ## P2 -- Medium Priority
 
-Improvements to usability, performance, and developer experience.
+Improvements to the API surface.
 
-### Backend
+### API improvements
 
-- **Add structured logging.** Replace `print()` calls throughout `analyzer.py`,
-  `serp_api.py`, and `llm.py` with Python `logging` so log levels and
-  formatting are consistent.
-- **Make LLM model configurable.** `llm.py` hardcodes
-  `anthropic/claude-3.5-sonnet`. Accept a `MODEL` environment variable to allow
-  switching models without code changes.
-- **SERP cache TTL is hardcoded to 24 hours.** Expose `SERP_CACHE_TTL_HOURS`
-  as an environment variable in `config.py`.
-- **Patent PDF storage.** PDFs are saved to a local `patents/` directory. For
-  containerized deployments, consider object storage (S3/MinIO) or at minimum
-  document the volume mount requirement more prominently.
-- **`analyze_single_patent` assumes local file path.** The method constructs
-  `patents/{patent_id}.pdf` and reads from disk, but does not download the PDF
-  first. Either integrate the download step or document the prerequisite.
-- **`Patent.patent_id` typed as `int` in `types.py` but used as `str`
-  everywhere.** Fix the type annotation to `str`.
-
-### Frontend
-
-- **No loading/error states on several pages.** The Batch and Analytics pages
-  would benefit from skeleton loaders and user-friendly error messages.
-- **No dark mode.** Tailwind is configured but no dark variant is applied.
-- **Missing `package-lock.json` or `pnpm-lock.yaml`.** The frontend has no
-  lockfile committed, leading to non-reproducible builds.
-
-### CI/CD
-
-- **No test stage in the Gitea Actions workflow.** `build.yaml` builds and
-  pushes images but never runs `pytest`. Add a test job that gates the build.
-- **No linting or type checking.** Add `ruff` (Python) and `tsc --noEmit`
-  (TypeScript) to CI.
+- **API pagination.** The `/analyze/batch` endpoint needs cursor-based
+  pagination for large result sets. The `/jobs` endpoint already has cursor
+  pagination. *(Issue #1669)*
+- **Request validation improvements.** Add stricter input validation for
+  company names (disallow special characters, enforce length limits).
+  *(Issue #1670)*
 
 ---
 
@@ -94,23 +132,20 @@ Improvements to usability, performance, and developer experience.
 
 Lower-urgency enhancements and future features.
 
-- **Export analysis reports.** Allow users to download analysis results as PDF
-  or CSV from the dashboard.
-- **Comparison view.** Side-by-side comparison of two companies' patent
-  portfolios.
-- **Scheduled/recurring analysis.** Periodically re-analyze tracked companies
-  and alert on significant changes.
-- **Webhook/notification support.** Send alerts (Slack, Discord, email) when
-  batch jobs complete or when a company's innovation score changes
-  significantly.
-- **Multi-model support.** Let users choose between LLM providers per analysis
-  (e.g., GPT-4o, Gemini, Claude) and compare outputs.
-- **Patent trend charts.** Visualize patent filing frequency and technology
-  category distribution over time in the Analytics page.
-- **API pagination.** The `/analyze/batch` and `/jobs` endpoints could benefit
-  from cursor-based pagination for large result sets.
-- **OpenAPI client generation.** Auto-generate the TypeScript API client from
-  the FastAPI OpenAPI spec to keep frontend types in sync.
+- **Historical analysis diffing.** Show what changed between two analysis runs
+  for the same company, highlighting new patents and score shifts.
+- **Patent classification tagging.** Automatically tag patents by technology
+  domain (AI, semiconductors, materials science) using LLM classification.
+- **User-level API keys.** Allow users to generate personal API keys for
+  programmatic access without JWT token refresh.
+- **Batch export.** Export analysis results for multiple companies at once as
+  a ZIP archive.
+- **Rate limiting dashboard.** Surface rate limit status and usage statistics
+  in the admin panel.
+- **Async webhook delivery.** Move webhook delivery to a background task queue
+  (e.g., Celery, arq) to avoid blocking the scheduler.
+- **Multi-tenant support.** Scope analysis results and tracked companies per
+  user or organization.
 
 ---
 

SPARC/analyzer.py

@@ -40,8 +40,9 @@ class CompanyAnalyzer:
         1. Retrieve patents from SERP API
         2. Download and parse each patent PDF
         3. Minimize patent content (remove bloat)
-        4. Analyze portfolio with LLM
-        5. Return performance estimation
+        4. Classify patent technology domain tags
+        5. Analyze portfolio with LLM
+        6. Return performance estimation
 
         Args:
           company_name: Name of the company to analyze
@@ -97,6 +98,17 @@ class CompanyAnalyzer:
         if not processed_patents:
             return f"Failed to process any patents for {company_name}"
 
+        # Classify each patent's technology domain tags
+        logger.info("Classifying patent technology domains...")
+        for patent_data in processed_patents:
+            if "tags" not in patent_data or not patent_data["tags"]:
+                tags = self.llm_analyzer.classify_patent_tags(
+                    patent_content=patent_data["content"], model=model
+                )
+                patent_data["tags"] = tags
+                # Persist tags to the database
+                self.db.update_patent_tags(patent_data["patent_id"], tags)
+
         logger.info("Analyzing portfolio with LLM...")
 
         # Analyze the full portfolio with LLM
@@ -181,7 +193,10 @@ class CompanyAnalyzer:
             if db:
                 cached = db.get_cached_patent(patent.patent_id)
                 if cached and cached.get("minimized_content"):
-                    return {"patent_id": patent.patent_id, "content": cached["minimized_content"]}
+                    result = {"patent_id": patent.patent_id, "content": cached["minimized_content"]}
+                    if cached.get("patent_tags"):
+                        result["tags"] = cached["patent_tags"]
+                    return result
 
             # Full processing: download, parse, minimize
             patent = SERP.save_patents(patent)
@@ -217,11 +232,19 @@ class CompanyAnalyzer:
             # Delegate to analyze_company which handles SERP/patent caching
             analysis = self.analyze_company(company_name, model=model)
 
-            # Determine patent count from cached SERP query
+            # Determine patent count and aggregate tags from cached SERP query
             query_hash = hashlib.sha256(company_name.lower().encode()).hexdigest()
             cached_ids = self.db.get_cached_serp_query(query_hash)
             patent_count = len(cached_ids) if cached_ids else 0
 
+            # Collect unique tags across all patents for this company
+            all_tags: set[str] = set()
+            if cached_ids:
+                for pid in cached_ids:
+                    cached_patent = self.db.get_cached_patent(pid)
+                    if cached_patent and cached_patent.get("patent_tags"):
+                        all_tags.update(cached_patent["patent_tags"])
+
             # Check if analysis indicates failure
             if analysis.startswith("No patents found") or analysis.startswith(
                 "Failed to process"
@@ -239,6 +262,7 @@ class CompanyAnalyzer:
                 analysis=analysis,
                 patent_count=patent_count,
                 success=True,
+                tags=sorted(all_tags),
             )
 
         except Exception as e:

SPARC/api.py

@@ -12,10 +12,10 @@ from typing import TYPE_CHECKING, Annotated, List
 if TYPE_CHECKING:
     from SPARC.database import DatabaseClient
 
-from fastapi import BackgroundTasks, Depends, FastAPI, HTTPException, Query, Request
+from fastapi import BackgroundTasks, Depends, FastAPI, HTTPException, Path, Query, Request
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import JSONResponse, StreamingResponse
-from pydantic import BaseModel, EmailStr, Field
+from pydantic import BaseModel, EmailStr, Field, StringConstraints
 from slowapi import Limiter
 from slowapi.errors import RateLimitExceeded
 from slowapi.util import get_remote_address
@@ -36,6 +36,16 @@ from SPARC.auth import (
 )
 from SPARC.types import BatchAnalysisResult, CompanyAnalysisResult
 
+# Validated company name type: 2-100 chars, alphanumeric + spaces/hyphens/ampersands/periods only.
+CompanyName = Annotated[
+    str,
+    StringConstraints(
+        min_length=2,
+        max_length=100,
+        pattern=r"^[a-zA-Z0-9][a-zA-Z0-9 \-&.]*$",
+    ),
+]
+
 
 # Pydantic models for API
 class CompanyAnalysisResponse(BaseModel):
@@ -47,6 +57,7 @@ class CompanyAnalysisResponse(BaseModel):
     success: bool
     error: str | None = None
     model: str | None = None
+    tags: list[str] = []
     timestamp: datetime
 
 
@@ -72,7 +83,7 @@ class CompanyAnalysisRequest(BaseModel):
 class BatchAnalysisRequest(BaseModel):
     """Request model for batch company analysis."""
 
-    companies: list[str] = Field(
+    companies: list[CompanyName] = Field(
         ..., min_length=1, max_length=20, description="List of company names to analyze"
     )
     max_workers: int = Field(
@@ -96,6 +107,24 @@ class JobStatus(BaseModel):
     error: str | None = None
 
 
+class AnalysisRecord(BaseModel):
+    """A single stored analysis result."""
+
+    id: int
+    company_name: str | None = None
+    analysis_type: str | None = None
+    model: str | None = None
+    response: str | None = None
+    timestamp: datetime | None = None
+
+
+class PaginatedAnalysisResponse(BaseModel):
+    """Paginated response for analysis result listings."""
+
+    items: list[AnalysisRecord]
+    next_cursor: str | None = None
+
+
 class PaginatedJobsResponse(BaseModel):
     """Paginated response for job listings."""
 
@@ -160,6 +189,7 @@ def _convert_result(result: CompanyAnalysisResult) -> CompanyAnalysisResponse:
         success=result.success,
         error=result.error,
         model=result.model,
+        tags=result.tags,
         timestamp=result.timestamp,
     )
 
@@ -217,10 +247,37 @@ app = FastAPI(
 limiter = Limiter(key_func=get_remote_address)
 app.state.limiter = limiter
 
+# In-memory rate limit statistics
+_rate_limit_stats: dict[str, dict] = {}
+
+
+def _track_rate_limit_request(endpoint: str, ip: str, rejected: bool = False) -> None:
+    """Record a request against a rate-limited endpoint."""
+    key = endpoint
+    if key not in _rate_limit_stats:
+        _rate_limit_stats[key] = {
+            "endpoint": endpoint,
+            "total_requests": 0,
+            "rejected_requests": 0,
+            "by_ip": {},
+        }
+    _rate_limit_stats[key]["total_requests"] += 1
+    if rejected:
+        _rate_limit_stats[key]["rejected_requests"] += 1
+    ip_stats = _rate_limit_stats[key].setdefault("by_ip", {})
+    if ip not in ip_stats:
+        ip_stats[ip] = {"total": 0, "rejected": 0}
+    ip_stats[ip]["total"] += 1
+    if rejected:
+        ip_stats[ip]["rejected"] += 1
+
 
 @app.exception_handler(RateLimitExceeded)
 async def rate_limit_handler(request: Request, exc: RateLimitExceeded):
     """Return 429 with Retry-After header when rate limit is exceeded."""
+    endpoint = request.url.path
+    ip = get_remote_address(request)
+    _track_rate_limit_request(endpoint, ip, rejected=True)
     retry_after = getattr(exc, "retry_after", 60)
     return JSONResponse(
         status_code=429,
@@ -249,6 +306,7 @@ async def register(request: Request, body: RegisterRequest):
 
     The first registered user automatically becomes an admin.
     """
+    _track_rate_limit_request("/auth/register", get_remote_address(request))
     db = get_db_client()
 
     # First user becomes admin
@@ -279,6 +337,7 @@ async def register(request: Request, body: RegisterRequest):
 @limiter.limit("10/minute")
 async def login(request: Request, body: LoginRequest):
     """Authenticate user and return JWT tokens."""
+    _track_rate_limit_request("/auth/login", get_remote_address(request))
     db = get_db_client()
 
     user = db.authenticate_user(body.email, body.password)
@@ -405,7 +464,7 @@ async def delete_user(
 class TrackCompanyRequest(BaseModel):
     """Request to add a company to tracking."""
 
-    company_name: str = Field(..., min_length=1, max_length=255)
+    company_name: CompanyName = Field(...)
 
 
 @app.get("/admin/tracked", tags=["Admin"])
@@ -432,7 +491,7 @@ async def add_tracked_company(
 
 @app.delete("/admin/tracked/{company_name}", tags=["Admin"])
 async def remove_tracked_company(
-    company_name: str,
+    company_name: Annotated[str, Path(min_length=2, max_length=100, pattern=r"^[a-zA-Z0-9][a-zA-Z0-9 \-&.]*$")],
     _: UserResponse = Depends(get_current_admin),
 ):
     """Remove a company from the tracked list (admin only)."""
@@ -443,6 +502,36 @@ async def remove_tracked_company(
     return {"message": f"Stopped tracking {company_name}"}
 
 
+@app.get("/admin/rate-limits", tags=["Admin"])
+async def get_rate_limit_stats(
+    _: UserResponse = Depends(get_current_admin),
+):
+    """Get rate limit status and usage statistics (admin only).
+
+    Returns current rate limit configuration and request statistics
+    for all rate-limited endpoints.
+
+    Returns:
+        List of rate limit stats per endpoint with total/rejected counts
+    """
+    rate_limits_config = {
+        "/auth/register": {"limit": "5/minute"},
+        "/auth/login": {"limit": "10/minute"},
+    }
+
+    results = []
+    for endpoint, conf in rate_limits_config.items():
+        stats = _rate_limit_stats.get(endpoint, {})
+        results.append({
+            "endpoint": endpoint,
+            "limit": conf["limit"],
+            "total_requests": stats.get("total_requests", 0),
+            "rejected_requests": stats.get("rejected_requests", 0),
+        })
+
+    return {"rate_limits": results}
+
+
 @app.get("/admin/alerts", tags=["Admin"])
 async def list_alerts(
     limit: int = Query(default=50, ge=1, le=200),
@@ -473,6 +562,38 @@ async def get_analytics(
     )
 
 
+@app.get("/analytics/tags", tags=["Analytics"])
+async def get_tag_distribution(
+    _: UserResponse = Depends(get_current_user),
+):
+    """Get the distribution of technology domain tags across all patents.
+
+    Returns:
+        List of tag counts and the canonical tag list
+    """
+    from SPARC.llm import LLMAnalyzer
+    db = get_db_client()
+
+    with db.get_conn() as conn:
+        with conn.cursor() as cur:
+            cur.execute(
+                """
+                SELECT tag, COUNT(*) as count
+                FROM patents, UNNEST(patent_tags) AS tag
+                WHERE patent_tags IS NOT NULL
+                GROUP BY tag
+                ORDER BY count DESC
+                """
+            )
+            rows = cur.fetchall()
+
+    by_tag = [{"tag": row[0], "count": row[1]} for row in rows]
+    return {
+        "by_tag": by_tag,
+        "canonical_tags": LLMAnalyzer.CANONICAL_TAGS,
+    }
+
+
 # ============== Model Selection Endpoints ==============
 
 # Supported models via OpenRouter
@@ -590,7 +711,7 @@ async def get_analytics_trends(
 
 @app.get("/export/{company_name}", tags=["Export"])
 async def export_company_csv(
-    company_name: str,
+    company_name: Annotated[str, Path(min_length=2, max_length=100, pattern=r"^[a-zA-Z0-9][a-zA-Z0-9 \-&.]*$")],
     _: UserResponse = Depends(get_current_user),
 ):
     """Export analysis results for a company as a CSV file.
@@ -642,7 +763,7 @@ async def export_company_csv(
 
 @app.get("/export/{company_name}/pdf", tags=["Export"])
 async def export_company_pdf(
-    company_name: str,
+    company_name: Annotated[str, Path(min_length=2, max_length=100, pattern=r"^[a-zA-Z0-9][a-zA-Z0-9 \-&.]*$")],
     _: UserResponse = Depends(get_current_user),
 ):
     """Export analysis results for a company as a formatted PDF report.
@@ -816,7 +937,7 @@ async def health_check():
     tags=["Analysis"],
 )
 async def analyze_company(
-    company_name: str,
+    company_name: Annotated[str, Path(min_length=2, max_length=100, pattern=r"^[a-zA-Z0-9][a-zA-Z0-9 \-&.]*$")],
     model: str | None = Query(default=None, description="LLM model to use (e.g. 'openai/gpt-4o'). Defaults to server config."),
     _: UserResponse = Depends(get_current_user),
 ):
@@ -846,7 +967,7 @@ async def analyze_company(
 )
 async def analyze_single_patent(
     patent_id: str,
-    company_name: str = Query(description="Company name for analysis context"),
+    company_name: Annotated[str, Query(min_length=2, max_length=100, pattern=r"^[a-zA-Z0-9][a-zA-Z0-9 \-&.]*$", description="Company name for analysis context")],
     _: UserResponse = Depends(get_current_user),
 ):
     """Analyze a single patent by its publication ID.
@@ -872,6 +993,75 @@ async def analyze_single_patent(
         raise HTTPException(status_code=404, detail=str(e))
 
 
+@app.get(
+    "/analyze/batch",
+    response_model=PaginatedAnalysisResponse,
+    tags=["Analysis"],
+)
+async def list_analysis_results(
+    company_name: Annotated[
+        str | None,
+        Query(description="Filter results by company name"),
+    ] = None,
+    tags: Annotated[
+        str | None,
+        Query(description="Comma-separated technology domain tags to filter by (e.g. 'ai,semiconductors')"),
+    ] = None,
+    limit: Annotated[int, Query(ge=1, le=200)] = 50,
+    cursor: Annotated[
+        str | None,
+        Query(description="Opaque cursor from a previous response's next_cursor field"),
+    ] = None,
+    _: UserResponse = Depends(get_current_user),
+):
+    """List stored analysis results with cursor-based pagination.
+
+    Returns past analysis results ordered by timestamp descending. Use
+    ``limit`` to control page size (default 50, max 200). The response
+    includes a ``next_cursor`` field; pass it back as the ``cursor`` query
+    parameter to fetch the next page. When ``next_cursor`` is ``null``,
+    there are no more results.
+
+    Args:
+        company_name: Optional filter by company name
+        tags: Optional comma-separated tag filter (e.g. 'ai,semiconductors')
+        limit: Maximum number of results to return (default 50, max 200)
+        cursor: Opaque pagination cursor from a previous response
+
+    Returns:
+        Paginated list of analysis results
+    """
+    # Parse and validate tags
+    tag_list = None
+    if tags:
+        from SPARC.llm import LLMAnalyzer
+        tag_list = [t.strip().lower() for t in tags.split(",") if t.strip()]
+        invalid = [t for t in tag_list if t not in LLMAnalyzer.CANONICAL_TAGS]
+        if invalid:
+            raise HTTPException(
+                status_code=400,
+                detail=f"Invalid tags: {', '.join(invalid)}. Valid tags: {', '.join(LLMAnalyzer.CANONICAL_TAGS)}",
+            )
+
+    db = _get_job_db()
+    rows = db.list_analyses(company_name=company_name, limit=limit + 1, cursor=cursor, tags=tag_list)
+
+    has_next = len(rows) > limit
+    if has_next:
+        rows = rows[:limit]
+
+    items = [AnalysisRecord(**row) for row in rows]
+
+    next_cursor = None
+    if has_next and rows:
+        last = rows[-1]
+        ts = last["timestamp"]
+        ts_str = ts.isoformat() if hasattr(ts, "isoformat") else str(ts)
+        next_cursor = f"{ts_str}|{last['id']}"
+
+    return PaginatedAnalysisResponse(items=items, next_cursor=next_cursor)
+
+
 @app.post(
     "/analyze/batch",
     response_model=BatchAnalysisResponse,
@@ -1047,7 +1237,7 @@ async def list_jobs(
         str | None,
         Query(description="Filter by status: pending, running, completed, failed"),
     ] = None,
-    limit: Annotated[int, Query(ge=1, le=100)] = 10,
+    limit: Annotated[int, Query(ge=1, le=200)] = 50,
     cursor: Annotated[
         str | None,
         Query(description="Opaque cursor from a previous response's next_cursor field"),

SPARC/database.py

@@ -146,15 +146,35 @@ class DatabaseClient:
                     pdf_link TEXT,
                     raw_sections JSONB,
                     minimized_content TEXT,
+                    patent_tags TEXT[],
                     created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
                 )
             """)
 
+            # Add patent_tags column if it doesn't exist (for existing tables)
+            cursor.execute("""
+                DO $$
+                BEGIN
+                    IF NOT EXISTS (
+                        SELECT 1 FROM information_schema.columns
+                        WHERE table_name = 'patents' AND column_name = 'patent_tags'
+                    ) THEN
+                        ALTER TABLE patents ADD COLUMN patent_tags TEXT[];
+                    END IF;
+                END $$;
+            """)
+
             cursor.execute("""
                 CREATE INDEX IF NOT EXISTS idx_patents_company
                 ON patents(company_name)
             """)
 
+            # GIN index for efficient tag array queries
+            cursor.execute("""
+                CREATE INDEX IF NOT EXISTS idx_patents_tags
+                ON patents USING GIN(patent_tags)
+            """)
+
             # Create SERP query cache table
             cursor.execute("""
                 CREATE TABLE IF NOT EXISTS serp_queries (
@@ -371,6 +391,60 @@ class DatabaseClient:
                 cursor.execute(query, params)
                 return [dict(row) for row in cursor.fetchall()]
 
+    def list_analyses(
+        self,
+        company_name: Optional[str] = None,
+        limit: int = 50,
+        cursor: Optional[str] = None,
+        tags: Optional[List[str]] = None,
+    ) -> List[Dict]:
+        """List analysis results with cursor-based pagination.
+
+        Args:
+            company_name: Optional filter by company name.
+            limit: Maximum number of records to return.
+            cursor: Opaque cursor (``timestamp|id``) from a previous response.
+            tags: Optional list of technology domain tags to filter by.
+
+        Returns:
+            List of analysis dicts ordered by timestamp descending.
+        """
+        conditions: list[str] = ["m.is_cached = FALSE"]
+        params: list = []
+        join_clause = ""
+
+        if company_name:
+            conditions.append("LOWER(m.company_name) = LOWER(%s)")
+            params.append(company_name)
+
+        if tags:
+            # Join with patents table to filter by tags
+            join_clause = (
+                " INNER JOIN patents p ON LOWER(p.company_name) = LOWER(m.company_name)"
+            )
+            conditions.append("p.patent_tags && %s")
+            params.append(tags)
+
+        if cursor:
+            try:
+                ts_str, cursor_id = cursor.rsplit("|", 1)
+                conditions.append("(m.timestamp, m.id) < (%s, %s)")
+                params.extend([ts_str, int(cursor_id)])
+            except (ValueError, TypeError):
+                pass  # Ignore malformed cursors; return from start
+
+        query = "SELECT DISTINCT m.id, m.company_name, m.analysis_type, m.model, m.response, m.timestamp FROM llm_messages m"
+        query += join_clause
+        if conditions:
+            query += " WHERE " + " AND ".join(conditions)
+        query += " ORDER BY m.timestamp DESC, m.id DESC LIMIT %s"
+        params.append(limit)
+
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cur:
+                cur.execute(query, params)
+                return [dict(row) for row in cur.fetchall()]
+
     def get_analytics(self, days: int = 30) -> Dict:
         """Get analytics on message usage.
 
@@ -451,22 +525,63 @@ class DatabaseClient:
         pdf_link: str,
         raw_sections: Dict,
         minimized_content: str,
+        patent_tags: Optional[List[str]] = None,
     ) -> None:
         """Store a processed patent in the cache."""
         with self.get_conn() as conn:
             with conn.cursor() as cursor:
                 cursor.execute(
                     """
-                    INSERT INTO patents (patent_id, company_name, pdf_link, raw_sections, minimized_content)
-                    VALUES (%s, %s, %s, %s, %s)
+                    INSERT INTO patents (patent_id, company_name, pdf_link, raw_sections, minimized_content, patent_tags)
+                    VALUES (%s, %s, %s, %s, %s, %s)
                     ON CONFLICT (patent_id) DO UPDATE SET
                         raw_sections = EXCLUDED.raw_sections,
-                        minimized_content = EXCLUDED.minimized_content
+                        minimized_content = EXCLUDED.minimized_content,
+                        patent_tags = EXCLUDED.patent_tags
                     """,
-                    (patent_id, company_name, pdf_link, json.dumps(raw_sections), minimized_content),
+                    (patent_id, company_name, pdf_link, json.dumps(raw_sections), minimized_content, patent_tags),
                 )
             conn.commit()
 
+    def update_patent_tags(self, patent_id: str, tags: List[str]) -> None:
+        """Update the technology domain tags for a patent."""
+        with self.get_conn() as conn:
+            with conn.cursor() as cursor:
+                cursor.execute(
+                    "UPDATE patents SET patent_tags = %s WHERE patent_id = %s",
+                    (tags, patent_id),
+                )
+            conn.commit()
+
+    def get_patents_by_tags(
+        self,
+        tags: List[str],
+        limit: int = 100,
+        offset: int = 0,
+    ) -> List[Dict]:
+        """Retrieve patents that match any of the given tags.
+
+        Args:
+            tags: List of tag strings to filter by (OR logic)
+            limit: Max results
+            offset: Pagination offset
+
+        Returns:
+            List of patent dicts
+        """
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
+                cursor.execute(
+                    """
+                    SELECT * FROM patents
+                    WHERE patent_tags && %s
+                    ORDER BY created_at DESC
+                    LIMIT %s OFFSET %s
+                    """,
+                    (tags, limit, offset),
+                )
+                return [dict(row) for row in cursor.fetchall()]
+
     def get_cached_serp_query(self, query_hash: str) -> Optional[List[str]]:
         """Look up cached SERP query results.
 

SPARC/llm.py

@@ -1,7 +1,8 @@
 """LLM integration for patent analysis using OpenRouter."""
 
+import json
 import logging
-from typing import Dict
+from typing import Dict, List
 
 from openai import OpenAI
 
@@ -245,4 +246,61 @@ Provide a comprehensive analysis (4-5 paragraphs) with a final verdict on the co
             metadata={**metadata, "pending": True}
         )
         return placeholder
-       
+
+    # Canonical technology domain tags
+    CANONICAL_TAGS = ["ai", "semiconductors", "materials", "biotech", "networking", "other"]
+
+    def classify_patent_tags(self, patent_content: str, model: str | None = None) -> List[str]:
+        """Classify a patent into one or more technology domain tags.
+
+        Sends the patent abstract/claims to the LLM with a classification prompt
+        and returns a list of canonical tags.
+
+        Args:
+          patent_content: Minimized patent text (abstract, claims, summary)
+          model: Optional model override
+
+        Returns:
+          List of canonical tag strings from CANONICAL_TAGS
+        """
+        prompt = f"""You are a patent classification system. Analyze the following patent content and assign one or more technology domain tags from this exact list:
+
+Tags: ai, semiconductors, materials, biotech, networking, other
+
+Rules:
+- Return ONLY a JSON array of tag strings, e.g. ["ai", "semiconductors"]
+- Use ONLY tags from the list above
+- Assign "other" only if no other tag fits
+- A patent can have multiple tags if it spans domains
+
+Patent Content:
+{patent_content}
+
+Return ONLY the JSON array, nothing else."""
+
+        effective_model = model or self.model
+
+        if self.test_mode:
+            logger.debug("TEST MODE - Classification prompt:\n%s", prompt)
+            return ["other"]
+
+        if self.client:
+            try:
+                response = self.client.chat.completions.create(
+                    model=effective_model,
+                    max_tokens=128,
+                    messages=[{"role": "user", "content": prompt}],
+                )
+                raw = response.choices[0].message.content.strip()
+                tags = json.loads(raw)
+                # Validate and filter to canonical tags only
+                valid_tags = [t for t in tags if t in self.CANONICAL_TAGS]
+                return valid_tags if valid_tags else ["other"]
+            except (json.JSONDecodeError, AttributeError, TypeError) as e:
+                logger.warning("Failed to parse classification response: %s", e)
+                return ["other"]
+            except Exception as e:
+                logger.warning("Classification LLM call failed: %s", e)
+                return ["other"]
+
+        return ["other"]

SPARC/types.py

@@ -25,6 +25,7 @@ class CompanyAnalysisResult:
     success: bool
     error: str | None = None
     model: str | None = None
+    tags: list[str] = field(default_factory=list)
     timestamp: datetime = field(default_factory=datetime.now)
 
 

frontend/src/api/client.ts

@@ -199,8 +199,18 @@ export const analyticsApi = {
     const response = await api.get<TrendData>(`/analytics/trends?days=${days}`);
     return response.data;
   },
+
+  getTagDistribution: async (): Promise<TagDistribution> => {
+    const response = await api.get<TagDistribution>('/analytics/tags');
+    return response.data;
+  },
 };
 
+export interface TagDistribution {
+  by_tag: Array<{ tag: string; count: number }>;
+  canonical_tags: string[];
+}
+
 // Admin API
 export const adminApi = {
   listUsers: async (limit = 100, offset = 0): Promise<User[]> => {

frontend/src/pages/Analytics.tsx

@@ -1,14 +1,24 @@
 import { useState } from 'react';
 import { useQuery } from '@tanstack/react-query';
 import { analyticsApi } from '../api/client';
-import { AlertCircle, Database } from 'lucide-react';
+import { AlertCircle, Database, Tag } from 'lucide-react';
 import { PieChart, Pie, Cell, BarChart, Bar, LineChart, Line, XAxis, YAxis, Tooltip, ResponsiveContainer, Legend } from 'recharts';
 import { useChartTheme } from '../context/useChartTheme';
 
 const COLORS = ['#6366f1', '#0ea5e9', '#10b981', '#f59e0b', '#ef4444', '#8b5cf6', '#ec4899', '#14b8a6'];
 
+const TAG_COLORS: Record<string, string> = {
+  ai: '#6366f1',
+  semiconductors: '#0ea5e9',
+  materials: '#10b981',
+  biotech: '#f59e0b',
+  networking: '#ec4899',
+  other: '#8b5cf6',
+};
+
 export function AnalyticsPage() {
   const [days, setDays] = useState(30);
+  const [selectedTags, setSelectedTags] = useState<string[]>([]);
   const chartTheme = useChartTheme();
 
   const { data, isLoading, isError, refetch } = useQuery({
@@ -21,6 +31,17 @@ export function AnalyticsPage() {
     queryFn: () => analyticsApi.getTrends(days),
   });
 
+  const tagQuery = useQuery({
+    queryKey: ['analytics-tags'],
+    queryFn: () => analyticsApi.getTagDistribution(),
+  });
+
+  const toggleTag = (tag: string) => {
+    setSelectedTags((prev) =>
+      prev.includes(tag) ? prev.filter((t) => t !== tag) : [...prev, tag]
+    );
+  };
+
   if (isLoading) {
     return (
       <div className="space-y-6">
@@ -107,6 +128,13 @@ export function AnalyticsPage() {
     count: t.count,
   }));
 
+  const tagData = tagQuery.data?.by_tag?.map((t) => ({
+    name: t.tag,
+    count: t.count,
+  })) || [];
+
+  const canonicalTags = tagQuery.data?.canonical_tags || [];
+
   return (
     <div className="space-y-6">
       {/* Header */}
@@ -131,6 +159,50 @@ export function AnalyticsPage() {
         </select>
       </div>
 
+      {/* Tag Filter Controls */}
+      {canonicalTags.length > 0 && (
+        <div className="bg-bg-card/60 border border-primary/15 rounded-2xl p-4">
+          <div className="flex items-center gap-2 mb-3">
+            <Tag size={16} className="text-primary" />
+            <span className="text-sm font-semibold text-text-primary">Filter by Technology Domain</span>
+            {selectedTags.length > 0 && (
+              <button
+                onClick={() => setSelectedTags([])}
+                className="ml-auto text-xs text-text-secondary hover:text-primary transition-colors"
+              >
+                Clear all
+              </button>
+            )}
+          </div>
+          <div className="flex flex-wrap gap-2">
+            {canonicalTags.map((tag) => {
+              const isActive = selectedTags.includes(tag);
+              const color = TAG_COLORS[tag] || '#8b5cf6';
+              const tagCount = tagQuery.data?.by_tag?.find((t) => t.tag === tag)?.count || 0;
+              return (
+                <button
+                  key={tag}
+                  onClick={() => toggleTag(tag)}
+                  className={`px-3 py-1.5 rounded-lg text-sm font-medium transition-all ${
+                    isActive
+                      ? 'text-white shadow-md'
+                      : 'bg-bg-card/80 text-text-secondary border border-primary/20 hover:border-primary/40'
+                  }`}
+                  style={isActive ? { backgroundColor: color } : {}}
+                >
+                  {tag}
+                  {tagCount > 0 && (
+                    <span className={`ml-1.5 text-xs ${isActive ? 'opacity-80' : 'opacity-60'}`}>
+                      ({tagCount})
+                    </span>
+                  )}
+                </button>
+              );
+            })}
+          </div>
+        </div>
+      )}
+
       {/* Summary Metrics */}
       <div className="grid grid-cols-1 md:grid-cols-3 gap-4">
         <MetricCard label="Total Analyses" value={data.total_messages} />
@@ -187,6 +259,28 @@ export function AnalyticsPage() {
             </ResponsiveContainer>
           </div>
         )}
+
+        {/* Bar Chart - Technology Domain Tags */}
+        {tagData.length > 0 && (
+          <div className="bg-bg-card/60 border border-primary/15 rounded-2xl p-6">
+            <h3 className="text-lg font-semibold text-text-primary mb-4">Patents by Technology Domain</h3>
+            <ResponsiveContainer width="100%" height={300}>
+              <BarChart data={tagData}>
+                <XAxis dataKey="name" stroke={chartTheme.axisStroke} fontSize={12} />
+                <YAxis stroke={chartTheme.axisStroke} fontSize={12} />
+                <Tooltip
+                  contentStyle={chartTheme.tooltipContentStyle}
+                  labelStyle={chartTheme.tooltipLabelStyle}
+                />
+                <Bar dataKey="count" radius={[4, 4, 0, 0]}>
+                  {tagData.map((entry, index) => (
+                    <Cell key={`tag-cell-${index}`} fill={TAG_COLORS[entry.name] || COLORS[index % COLORS.length]} />
+                  ))}
+                </Bar>
+              </BarChart>
+            </ResponsiveContainer>
+          </div>
+        )}
       </div>
 
       {/* Trend Charts */}

tests/test_analyze_single_patent.py

@@ -0,0 +1,211 @@
+"""Tests for analyze_single_patent auto-download path.
+
+Covers issue #1661:
+- PDF exists on disk: direct analysis (happy path)
+- PDF not on disk, cached link exists: auto-download and analyze
+- PDF not on disk, no cached link: FileNotFoundError
+- Analysis failure after PDF found: graceful error message
+- Model override parameter passthrough
+"""
+
+import os
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from SPARC.analyzer import CompanyAnalyzer
+from SPARC.types import Patent
+
+
+@pytest.fixture(autouse=True)
+def mock_db(mocker):
+    """Mock DatabaseClient so no real DB is needed."""
+    mock_db_cls = mocker.patch("SPARC.analyzer.DatabaseClient")
+    mock_db_instance = MagicMock()
+    mock_db_instance.get_cached_patent.return_value = None
+    mock_db_instance.get_cached_serp_query.return_value = None
+    mock_db_cls.return_value = mock_db_instance
+    return mock_db_instance
+
+
+@pytest.fixture
+def analyzer(mocker, mock_db):
+    """Create a CompanyAnalyzer with mocked LLM and DB."""
+    mocker.patch("SPARC.analyzer.LLMAnalyzer")
+    return CompanyAnalyzer(openrouter_api_key="test-key")
+
+
+class TestAnalyzeSinglePatentAutoDownload:
+    """Test the auto-download logic in analyze_single_patent."""
+
+    def test_pdf_on_disk_analyzed_directly(self, analyzer, mocker, tmp_path):
+        """When PDF exists on disk, it is analyzed directly without download."""
+        patent_id = "US-11234567-B2"
+
+        # Create the patents dir and PDF file
+        patents_dir = tmp_path / "patents"
+        patents_dir.mkdir()
+        pdf_path = patents_dir / f"{patent_id}.pdf"
+        pdf_path.write_bytes(b"fake PDF content")
+
+        mock_parse = mocker.patch("SPARC.analyzer.SERP.parse_patent_pdf")
+        mock_minimize = mocker.patch("SPARC.analyzer.SERP.minimize_patent_for_llm")
+        mock_parse.return_value = {"abstract": "test", "claims": "test claims"}
+        mock_minimize.return_value = "minimized content"
+        analyzer.llm_analyzer.analyze_patent_content.return_value = "Good patent."
+
+        # Change cwd so patents/{patent_id}.pdf resolves to our tmp_path
+        original_cwd = os.getcwd()
+        os.chdir(tmp_path)
+        try:
+            result = analyzer.analyze_single_patent(patent_id, "TestCo")
+        finally:
+            os.chdir(original_cwd)
+
+        assert result == "Good patent."
+        # DB cache should not have been queried since file existed
+        analyzer.db.get_cached_patent.assert_not_called()
+
+    def test_auto_download_from_cached_link(self, analyzer, mocker, tmp_path):
+        """When PDF is not on disk but link is cached, auto-download occurs."""
+        patent_id = "US-99887766-A1"
+
+        # No patents dir exists (PDF not on disk)
+        mock_save = mocker.patch("SPARC.analyzer.SERP.save_patents")
+        downloaded_patent = Patent(patent_id=patent_id, pdf_link="https://example.com/patent.pdf")
+        downloaded_patent.pdf_path = f"patents/{patent_id}.pdf"
+        mock_save.return_value = downloaded_patent
+
+        # Cached patent has a PDF link
+        analyzer.db.get_cached_patent.return_value = {
+            "patent_id": patent_id,
+            "pdf_link": "https://example.com/patent.pdf",
+        }
+
+        # Mock the rest of the analysis pipeline
+        mock_parse = mocker.patch("SPARC.analyzer.SERP.parse_patent_pdf")
+        mock_minimize = mocker.patch("SPARC.analyzer.SERP.minimize_patent_for_llm")
+        mock_parse.return_value = {"abstract": "test abstract"}
+        mock_minimize.return_value = "minimized content"
+        analyzer.llm_analyzer.analyze_patent_content.return_value = "Strong innovation."
+
+        # Change cwd so patents/{patent_id}.pdf does NOT exist
+        original_cwd = os.getcwd()
+        os.chdir(tmp_path)
+        try:
+            result = analyzer.analyze_single_patent(patent_id, "DownloadCo")
+        finally:
+            os.chdir(original_cwd)
+
+        assert result == "Strong innovation."
+        analyzer.db.get_cached_patent.assert_called_once_with(patent_id)
+        mock_save.assert_called_once()
+        # Verify the Patent passed to save_patents has the correct ID and link
+        saved_patent = mock_save.call_args[0][0]
+        assert saved_patent.patent_id == patent_id
+        assert saved_patent.pdf_link == "https://example.com/patent.pdf"
+
+    def test_no_cached_link_raises_file_not_found(self, analyzer, mocker, tmp_path):
+        """When PDF is not on disk and no cached link, FileNotFoundError raised."""
+        patent_id = "US-00000000-X1"
+
+        analyzer.db.get_cached_patent.return_value = None
+
+        original_cwd = os.getcwd()
+        os.chdir(tmp_path)
+        try:
+            with pytest.raises(FileNotFoundError, match="no download link is cached"):
+                analyzer.analyze_single_patent(patent_id, "MissingCo")
+        finally:
+            os.chdir(original_cwd)
+
+    def test_cached_patent_without_pdf_link_raises(self, analyzer, mocker, tmp_path):
+        """When cached patent exists but has no pdf_link, FileNotFoundError raised."""
+        patent_id = "US-11111111-B1"
+
+        analyzer.db.get_cached_patent.return_value = {
+            "patent_id": patent_id,
+            "pdf_link": None,
+        }
+
+        original_cwd = os.getcwd()
+        os.chdir(tmp_path)
+        try:
+            with pytest.raises(FileNotFoundError, match="no download link is cached"):
+                analyzer.analyze_single_patent(patent_id, "NoPDFCo")
+        finally:
+            os.chdir(original_cwd)
+
+    def test_analysis_exception_returns_error_message(self, analyzer, mocker, tmp_path):
+        """When analysis pipeline fails, returns error string instead of raising."""
+        patent_id = "US-22222222-A2"
+
+        # Create the PDF on disk so it skips download
+        patents_dir = tmp_path / "patents"
+        patents_dir.mkdir()
+        (patents_dir / f"{patent_id}.pdf").write_bytes(b"fake PDF")
+
+        # Parse fails
+        mocker.patch(
+            "SPARC.analyzer.SERP.parse_patent_pdf",
+            side_effect=ValueError("Corrupt PDF"),
+        )
+
+        original_cwd = os.getcwd()
+        os.chdir(tmp_path)
+        try:
+            result = analyzer.analyze_single_patent(patent_id, "ErrorCo")
+        finally:
+            os.chdir(original_cwd)
+
+        assert "Failed to analyze patent" in result
+        assert "Corrupt PDF" in result
+
+    def test_model_override_passed_to_llm(self, analyzer, mocker, tmp_path):
+        """The model parameter is forwarded to the LLM analyzer."""
+        patent_id = "US-33333333-B2"
+
+        patents_dir = tmp_path / "patents"
+        patents_dir.mkdir()
+        (patents_dir / f"{patent_id}.pdf").write_bytes(b"fake PDF")
+
+        mocker.patch("SPARC.analyzer.SERP.parse_patent_pdf", return_value={"abstract": "test"})
+        mocker.patch("SPARC.analyzer.SERP.minimize_patent_for_llm", return_value="content")
+        analyzer.llm_analyzer.analyze_patent_content.return_value = "Analysis result."
+
+        original_cwd = os.getcwd()
+        os.chdir(tmp_path)
+        try:
+            result = analyzer.analyze_single_patent(
+                patent_id, "ModelCo", model="openai/gpt-4o"
+            )
+        finally:
+            os.chdir(original_cwd)
+
+        assert result == "Analysis result."
+        analyzer.llm_analyzer.analyze_patent_content.assert_called_once_with(
+            patent_content="content",
+            company_name="ModelCo",
+            model="openai/gpt-4o",
+        )
+
+    def test_file_not_found_during_parse_re_raised(self, analyzer, mocker, tmp_path):
+        """FileNotFoundError during parsing is re-raised, not caught."""
+        patent_id = "US-44444444-C1"
+
+        patents_dir = tmp_path / "patents"
+        patents_dir.mkdir()
+        (patents_dir / f"{patent_id}.pdf").write_bytes(b"fake PDF")
+
+        mocker.patch(
+            "SPARC.analyzer.SERP.parse_patent_pdf",
+            side_effect=FileNotFoundError("PDF file vanished"),
+        )
+
+        original_cwd = os.getcwd()
+        os.chdir(tmp_path)
+        try:
+            with pytest.raises(FileNotFoundError, match="PDF file vanished"):
+                analyzer.analyze_single_patent(patent_id, "VanishCo")
+        finally:
+            os.chdir(original_cwd)

tests/test_company_name_validation.py

@@ -0,0 +1,157 @@
+"""Tests for company name input validation on analysis endpoints."""
+
+from datetime import datetime
+from unittest.mock import Mock
+
+import pytest
+from fastapi.testclient import TestClient
+
+from SPARC.api import app
+from SPARC.types import CompanyAnalysisResult
+
+
+@pytest.fixture
+def client():
+    """Create test client."""
+    return TestClient(app)
+
+
+@pytest.fixture
+def mock_analyzer(mocker):
+    """Mock the global analyzer so valid requests succeed."""
+    mock = Mock()
+    mock._analyze_company_safe.return_value = CompanyAnalysisResult(
+        company_name="nvidia",
+        analysis="Test analysis",
+        patent_count=1,
+        success=True,
+        timestamp=datetime.now(),
+    )
+    mocker.patch("SPARC.api._analyzer", mock)
+    return mock
+
+
+class TestCompanyNameValidation:
+    """Test that company names are validated on analysis endpoints."""
+
+    # --- Too short ---
+
+    def test_single_char_rejected(self, client, mock_analyzer):
+        """A one-character company name should be rejected."""
+        response = client.get("/analyze/X")
+        assert response.status_code == 422
+
+    # --- Too long ---
+
+    def test_over_100_chars_rejected(self, client, mock_analyzer):
+        """A company name longer than 100 characters should be rejected."""
+        long_name = "A" * 101
+        response = client.get(f"/analyze/{long_name}")
+        assert response.status_code == 422
+
+    # --- Special characters ---
+
+    @pytest.mark.parametrize(
+        "bad_name",
+        [
+            "nvidia!",
+            "intel@corp",
+            "test#company",
+            "foo$bar",
+            "a%b",
+            "x^y",
+            "semi;colon",
+            "drop'table",
+            'say"hello',
+            "path/traversal",
+            "back\\slash",
+            "pipe|char",
+            "star*glob",
+            "question?mark",
+            "<script>",
+            "curly{brace}",
+            "equal=sign",
+            "plus+plus",
+            "comma,separated",
+        ],
+    )
+    def test_special_chars_rejected(self, client, mock_analyzer, bad_name):
+        """Company names with disallowed special characters should be rejected."""
+        response = client.get(f"/analyze/{bad_name}")
+        assert response.status_code == 422
+
+    # --- Valid names ---
+
+    @pytest.mark.parametrize(
+        "valid_name",
+        [
+            "nvidia",
+            "Intel",
+            "TSMC",
+            "Texas Instruments",
+            "Johnson-Johnson",
+            "AT&T",
+            "St. Jude Medical",
+            "3M",
+            "21st Century Fox",
+            "ab",  # minimum length
+            "A" * 100,  # maximum length
+        ],
+    )
+    def test_valid_names_accepted(self, client, mock_analyzer, valid_name):
+        """Valid company names should be accepted (200, not 422)."""
+        response = client.get(f"/analyze/{valid_name}")
+        # Should not be a validation error; 200 or other non-422 status is fine
+        assert response.status_code != 422
+
+    # --- Batch endpoint validation ---
+
+    def test_batch_too_short_rejected(self, client, mock_analyzer):
+        """Batch endpoint should reject company names that are too short."""
+        response = client.post(
+            "/analyze/batch",
+            json={"companies": ["X"]},
+        )
+        assert response.status_code == 422
+
+    def test_batch_too_long_rejected(self, client, mock_analyzer):
+        """Batch endpoint should reject company names that are too long."""
+        response = client.post(
+            "/analyze/batch",
+            json={"companies": ["A" * 101]},
+        )
+        assert response.status_code == 422
+
+    def test_batch_special_chars_rejected(self, client, mock_analyzer):
+        """Batch endpoint should reject company names with special chars."""
+        response = client.post(
+            "/analyze/batch",
+            json={"companies": ["nvidia!", "intel"]},
+        )
+        assert response.status_code == 422
+
+    def test_batch_valid_names_accepted(self, client, mock_analyzer):
+        """Batch endpoint should accept valid company names."""
+        response = client.post(
+            "/analyze/batch",
+            json={"companies": ["nvidia", "Intel", "AT&T"]},
+        )
+        assert response.status_code != 422
+
+    # --- Name must start with alphanumeric ---
+
+    def test_leading_space_rejected(self, client, mock_analyzer):
+        """Company name starting with a space should be rejected."""
+        response = client.post(
+            "/analyze/batch",
+            json={"companies": [" nvidia"]},
+        )
+        assert response.status_code == 422
+
+    def test_leading_hyphen_rejected(self, client, mock_analyzer):
+        """Company name starting with a hyphen should be rejected."""
+        response = client.post(
+            "/analyze/batch",
+            json={"companies": ["-nvidia"]},
+        )
+        assert response.status_code == 422

tests/test_export.py

@@ -0,0 +1,224 @@
+"""Tests for export endpoints: CSV and PDF export of analysis results.
+
+Covers issue #1655:
+- GET /export/{company_name} (CSV export)
+- GET /export/{company_name}/pdf (PDF export)
+
+All tests mock the database layer and use JWT auth fixtures from test_auth patterns.
+"""
+
+from datetime import datetime, timezone
+from unittest.mock import MagicMock, patch
+
+import pytest
+from fastapi.testclient import TestClient
+
+from SPARC.api import app
+from SPARC.auth import create_access_token
+
+
+@pytest.fixture
+def client():
+    """Create test client."""
+    return TestClient(app)
+
+
+@pytest.fixture(autouse=True)
+def mock_db():
+    """Mock the database client used by export and auth endpoints."""
+    db = MagicMock()
+
+    # Default: user exists for auth
+    db.get_user_by_id.return_value = {
+        "id": 1,
+        "email": "user@test.com",
+        "role": "user",
+        "created_at": datetime(2025, 1, 1, tzinfo=timezone.utc),
+    }
+
+    # Mock get_conn for export queries
+    mock_cursor = MagicMock()
+    mock_conn = MagicMock()
+    mock_conn.cursor.return_value.__enter__ = MagicMock(return_value=mock_cursor)
+    mock_conn.cursor.return_value.__exit__ = MagicMock(return_value=False)
+    db.get_conn.return_value.__enter__ = MagicMock(return_value=mock_conn)
+    db.get_conn.return_value.__exit__ = MagicMock(return_value=False)
+    db._mock_cursor = mock_cursor
+
+    with patch("SPARC.api.get_db_client", return_value=db), \
+         patch("SPARC.auth.get_db_client", return_value=db):
+        yield db
+
+
+def _auth_header():
+    """Create an Authorization header with a valid access token."""
+    token = create_access_token(1, "user@test.com", "user")
+    return {"Authorization": f"Bearer {token}"}
+
+
+def _sample_rows():
+    """Return sample llm_messages rows as tuples (matching cursor.fetchall format)."""
+    return [
+        (
+            "NVIDIA",
+            "company_analysis",
+            "anthropic/claude-3.5-sonnet",
+            "Strong AI patent portfolio with focus on GPU architectures.",
+            datetime(2025, 6, 15, 10, 30, 0),
+        ),
+        (
+            "NVIDIA",
+            "patent_analysis",
+            "openai/gpt-4o",
+            "Patent US-12345678-B2 covers novel tensor core design.",
+            datetime(2025, 6, 14, 9, 0, 0),
+        ),
+    ]
+
+
+class TestCSVExport:
+    """GET /export/{company_name} -- CSV export."""
+
+    def test_csv_export_success(self, client, mock_db):
+        """Valid company with results returns a CSV file."""
+        mock_db._mock_cursor.fetchall.return_value = _sample_rows()
+
+        response = client.get("/export/NVIDIA", headers=_auth_header())
+
+        assert response.status_code == 200
+        assert response.headers["content-type"].startswith("text/csv")
+        assert "attachment" in response.headers.get("content-disposition", "")
+        assert "sparc_nvidia_export.csv" in response.headers["content-disposition"]
+
+        # Verify CSV content (CSV uses \r\n line endings)
+        lines = response.text.strip().split("\n")
+        assert len(lines) == 3  # header + 2 data rows
+        assert lines[0].strip() == "company_name,analysis_type,model,analysis,timestamp"
+        assert "NVIDIA" in lines[1]
+        assert "company_analysis" in lines[1]
+
+    def test_csv_export_no_results_returns_404(self, client, mock_db):
+        """Unknown company returns 404."""
+        mock_db._mock_cursor.fetchall.return_value = []
+
+        response = client.get("/export/nonexistent", headers=_auth_header())
+
+        assert response.status_code == 404
+        assert "No analysis results found" in response.json()["detail"]
+
+    def test_csv_export_unauthenticated_returns_401(self, client):
+        """Request without token returns 401."""
+        response = client.get("/export/NVIDIA")
+        assert response.status_code == 401
+
+    def test_csv_export_invalid_token_returns_401(self, client):
+        """Request with invalid token returns 401."""
+        response = client.get(
+            "/export/NVIDIA",
+            headers={"Authorization": "Bearer invalid.token.here"},
+        )
+        assert response.status_code == 401
+
+    def test_csv_export_filename_sanitization(self, client, mock_db):
+        """Company names with spaces get sanitized in the filename."""
+        mock_db._mock_cursor.fetchall.return_value = [
+            (
+                "Tesla Motors",
+                "company_analysis",
+                "anthropic/claude-3.5-sonnet",
+                "EV patent portfolio analysis.",
+                datetime(2025, 6, 15, 10, 0, 0),
+            ),
+        ]
+
+        response = client.get("/export/Tesla Motors", headers=_auth_header())
+
+        assert response.status_code == 200
+        assert "tesla_motors" in response.headers["content-disposition"]
+
+    def test_csv_export_single_row(self, client, mock_db):
+        """Single analysis result produces valid CSV with one data row."""
+        mock_db._mock_cursor.fetchall.return_value = [_sample_rows()[0]]
+
+        response = client.get("/export/NVIDIA", headers=_auth_header())
+
+        assert response.status_code == 200
+        lines = response.text.strip().split("\n")
+        assert len(lines) == 2  # header + 1 data row
+
+
+class TestPDFExport:
+    """GET /export/{company_name}/pdf -- PDF report export."""
+
+    def test_pdf_export_success(self, client, mock_db):
+        """Valid company with results returns a PDF file."""
+        mock_db._mock_cursor.fetchall.return_value = _sample_rows()
+
+        response = client.get("/export/NVIDIA/pdf", headers=_auth_header())
+
+        assert response.status_code == 200
+        assert response.headers["content-type"] == "application/pdf"
+        assert "attachment" in response.headers.get("content-disposition", "")
+        # PDF files start with %PDF
+        assert response.content[:4] == b"%PDF"
+
+    def test_pdf_export_no_results_returns_404(self, client, mock_db):
+        """Unknown company returns 404."""
+        mock_db._mock_cursor.fetchall.return_value = []
+
+        response = client.get("/export/nonexistent/pdf", headers=_auth_header())
+
+        assert response.status_code == 404
+        assert "No analysis results found" in response.json()["detail"]
+
+    def test_pdf_export_unauthenticated_returns_401(self, client):
+        """Request without token returns 401."""
+        response = client.get("/export/NVIDIA/pdf")
+        assert response.status_code == 401
+
+    def test_pdf_export_invalid_token_returns_401(self, client):
+        """Request with invalid token returns 401."""
+        response = client.get(
+            "/export/NVIDIA/pdf",
+            headers={"Authorization": "Bearer invalid.token.here"},
+        )
+        assert response.status_code == 401
+
+    def test_pdf_export_filename_contains_date(self, client, mock_db):
+        """PDF filename includes the analysis date."""
+        mock_db._mock_cursor.fetchall.return_value = _sample_rows()
+
+        response = client.get("/export/NVIDIA/pdf", headers=_auth_header())
+
+        assert response.status_code == 200
+        disposition = response.headers["content-disposition"]
+        assert "nvidia-analysis-" in disposition
+        assert ".pdf" in disposition
+
+    def test_pdf_export_special_chars_in_response(self, client, mock_db):
+        """Analysis text with XML-special chars (<, >, &) does not break PDF generation."""
+        rows = [
+            (
+                "TestCo",
+                "company_analysis",
+                "anthropic/claude-3.5-sonnet",
+                "Revenue > $1B & growth <20% for Q4. Test <html> escaping.",
+                datetime(2025, 6, 15, 10, 0, 0),
+            ),
+        ]
+        mock_db._mock_cursor.fetchall.return_value = rows
+
+        response = client.get("/export/TestCo/pdf", headers=_auth_header())
+
+        assert response.status_code == 200
+        assert response.content[:4] == b"%PDF"
+
+    def test_pdf_export_multiple_analyses(self, client, mock_db):
+        """Multiple analysis records produce a valid PDF with content."""
+        mock_db._mock_cursor.fetchall.return_value = _sample_rows()
+
+        response = client.get("/export/NVIDIA/pdf", headers=_auth_header())
+
+        assert response.status_code == 200
+        # PDF should have reasonable size (more than just headers)
+        assert len(response.content) > 500

tests/test_pagination.py

@@ -0,0 +1,169 @@
+"""Tests for cursor-based pagination on /analyze/batch GET and /jobs endpoints."""
+
+from datetime import datetime, timedelta
+from unittest.mock import Mock, patch
+
+import pytest
+from fastapi.testclient import TestClient
+
+from SPARC.api import app
+
+
+@pytest.fixture
+def client():
+    """Create test client."""
+    return TestClient(app)
+
+
+def _make_analysis_row(id_: int, minutes_ago: int = 0, company: str = "nvidia"):
+    """Create a fake analysis row dict."""
+    ts = datetime.now() - timedelta(minutes=minutes_ago)
+    return {
+        "id": id_,
+        "company_name": company,
+        "analysis_type": "patent_portfolio",
+        "model": "openai/gpt-4o",
+        "response": f"Analysis for {company}",
+        "timestamp": ts,
+    }
+
+
+def _make_job_row(job_id: str, minutes_ago: int = 0, status: str = "completed"):
+    """Create a fake job row dict."""
+    ts = datetime.now() - timedelta(minutes=minutes_ago)
+    return {
+        "job_id": job_id,
+        "status": status,
+        "progress": 100 if status == "completed" else 0,
+        "total_companies": 1,
+        "completed_companies": 1 if status == "completed" else 0,
+        "result": None,
+        "error": None,
+        "created_at": ts,
+    }
+
+
+class TestAnalyzeBatchGetPagination:
+    """Test cursor-based pagination on GET /analyze/batch."""
+
+    @patch("SPARC.api._get_job_db")
+    def test_returns_items_and_no_cursor_when_less_than_limit(self, mock_get_db, client):
+        """When fewer results than limit, next_cursor should be null."""
+        db = Mock()
+        db.list_analyses.return_value = [
+            _make_analysis_row(1, minutes_ago=10),
+            _make_analysis_row(2, minutes_ago=20),
+        ]
+        mock_get_db.return_value = db
+
+        response = client.get("/analyze/batch?limit=10")
+        assert response.status_code == 200
+        data = response.json()
+        assert len(data["items"]) == 2
+        assert data["next_cursor"] is None
+
+    @patch("SPARC.api._get_job_db")
+    def test_returns_cursor_when_more_results_exist(self, mock_get_db, client):
+        """When more results exist than limit, next_cursor should be set."""
+        db = Mock()
+        # Return limit+1 rows to simulate more data
+        rows = [_make_analysis_row(i, minutes_ago=i) for i in range(4)]
+        db.list_analyses.return_value = rows
+        mock_get_db.return_value = db
+
+        response = client.get("/analyze/batch?limit=3")
+        assert response.status_code == 200
+        data = response.json()
+        assert len(data["items"]) == 3
+        assert data["next_cursor"] is not None
+
+    @patch("SPARC.api._get_job_db")
+    def test_cursor_passed_to_db(self, mock_get_db, client):
+        """The cursor query param should be forwarded to the database layer."""
+        db = Mock()
+        db.list_analyses.return_value = []
+        mock_get_db.return_value = db
+
+        client.get("/analyze/batch?cursor=2025-01-01T00:00:00|42")
+        db.list_analyses.assert_called_once()
+        call_kwargs = db.list_analyses.call_args
+        assert call_kwargs.kwargs.get("cursor") == "2025-01-01T00:00:00|42" or \
+            (call_kwargs[1].get("cursor") == "2025-01-01T00:00:00|42" if len(call_kwargs) > 1 else False)
+
+    @patch("SPARC.api._get_job_db")
+    def test_default_limit_is_50(self, mock_get_db, client):
+        """Default limit should be 50."""
+        db = Mock()
+        db.list_analyses.return_value = []
+        mock_get_db.return_value = db
+
+        client.get("/analyze/batch")
+        call_kwargs = db.list_analyses.call_args
+        # The endpoint requests limit+1 from DB, so 51
+        assert 51 in call_kwargs.args or call_kwargs.kwargs.get("limit") == 51
+
+    def test_limit_over_200_rejected(self, client):
+        """Limit > 200 should be rejected with 422."""
+        response = client.get("/analyze/batch?limit=201")
+        assert response.status_code == 422
+
+    def test_limit_zero_rejected(self, client):
+        """Limit < 1 should be rejected with 422."""
+        response = client.get("/analyze/batch?limit=0")
+        assert response.status_code == 422
+
+    @patch("SPARC.api._get_job_db")
+    def test_company_name_filter(self, mock_get_db, client):
+        """The company_name filter should be forwarded to the database."""
+        db = Mock()
+        db.list_analyses.return_value = []
+        mock_get_db.return_value = db
+
+        client.get("/analyze/batch?company_name=intel")
+        call_kwargs = db.list_analyses.call_args
+        assert call_kwargs.kwargs.get("company_name") == "intel" or \
+            "intel" in (call_kwargs.args if call_kwargs.args else [])
+
+    @patch("SPARC.api._get_job_db")
+    def test_empty_result_set(self, mock_get_db, client):
+        """Empty result set returns empty items and null cursor."""
+        db = Mock()
+        db.list_analyses.return_value = []
+        mock_get_db.return_value = db
+
+        response = client.get("/analyze/batch")
+        assert response.status_code == 200
+        data = response.json()
+        assert data["items"] == []
+        assert data["next_cursor"] is None
+
+
+class TestJobsPaginationDefaults:
+    """Test that /jobs endpoint uses updated defaults."""
+
+    @patch("SPARC.api._get_job_db")
+    def test_default_limit_is_50(self, mock_get_db, client):
+        """Default limit should now be 50."""
+        db = Mock()
+        db.list_jobs.return_value = []
+        mock_get_db.return_value = db
+
+        client.get("/jobs")
+        call_kwargs = db.list_jobs.call_args
+        # Endpoint requests limit+1 from DB, so 51
+        assert 51 in call_kwargs.args or call_kwargs.kwargs.get("limit") == 51
+
+    def test_limit_over_200_rejected(self, client):
+        """Limit > 200 should be rejected with 422."""
+        response = client.get("/jobs?limit=201")
+        assert response.status_code == 422
+
+    @patch("SPARC.api._get_job_db")
+    def test_limit_200_accepted(self, mock_get_db, client):
+        """Limit of exactly 200 should be accepted."""
+        db = Mock()
+        db.list_jobs.return_value = []
+        mock_get_db.return_value = db
+
+        response = client.get("/jobs?limit=200")
+        assert response.status_code == 200

tests/test_patent_tags.py

@@ -0,0 +1,262 @@
+"""Tests for LLM-based patent classification tagging by technology domain."""
+
+import json
+from unittest.mock import MagicMock, Mock, patch
+
+import pytest
+
+from SPARC.llm import LLMAnalyzer
+
+
+class TestClassifyPatentTags:
+    """Test the classify_patent_tags method on LLMAnalyzer."""
+
+    @pytest.fixture(autouse=True)
+    def mock_database(self, mocker):
+        """Mock the database client for all tests."""
+        mock_db_client = Mock()
+        mock_db_client.get_cached_response.return_value = None
+        mock_db_client.store_message.return_value = 1
+        mocker.patch("SPARC.llm.DatabaseClient", return_value=mock_db_client)
+        return mock_db_client
+
+    def test_classify_returns_valid_tags(self, mocker, mock_database):
+        """Test that classify_patent_tags returns valid canonical tags from LLM."""
+        mock_openai = mocker.patch("SPARC.llm.OpenAI")
+        mock_client = Mock()
+        mock_openai.return_value = mock_client
+
+        mock_response = Mock()
+        mock_response.choices = [Mock(message=Mock(content='["ai", "semiconductors"]'))]
+        mock_client.chat.completions.create.return_value = mock_response
+
+        analyzer = LLMAnalyzer(api_key="test-key")
+        tags = analyzer.classify_patent_tags("A patent about neural network accelerator chips")
+
+        assert tags == ["ai", "semiconductors"]
+        mock_client.chat.completions.create.assert_called_once()
+
+        # Verify the prompt contains classification instructions
+        call_args = mock_client.chat.completions.create.call_args
+        prompt_text = call_args[1]["messages"][0]["content"]
+        assert "ai" in prompt_text
+        assert "semiconductors" in prompt_text
+        assert "JSON array" in prompt_text
+
+    def test_classify_filters_invalid_tags(self, mocker, mock_database):
+        """Test that invalid tags from LLM response are filtered out."""
+        mock_openai = mocker.patch("SPARC.llm.OpenAI")
+        mock_client = Mock()
+        mock_openai.return_value = mock_client
+
+        mock_response = Mock()
+        mock_response.choices = [Mock(message=Mock(content='["ai", "quantum_computing", "biotech"]'))]
+        mock_client.chat.completions.create.return_value = mock_response
+
+        analyzer = LLMAnalyzer(api_key="test-key")
+        tags = analyzer.classify_patent_tags("Some patent content")
+
+        assert tags == ["ai", "biotech"]
+        assert "quantum_computing" not in tags
+
+    def test_classify_returns_other_when_all_invalid(self, mocker, mock_database):
+        """Test fallback to 'other' when all LLM tags are invalid."""
+        mock_openai = mocker.patch("SPARC.llm.OpenAI")
+        mock_client = Mock()
+        mock_openai.return_value = mock_client
+
+        mock_response = Mock()
+        mock_response.choices = [Mock(message=Mock(content='["quantum", "robotics"]'))]
+        mock_client.chat.completions.create.return_value = mock_response
+
+        analyzer = LLMAnalyzer(api_key="test-key")
+        tags = analyzer.classify_patent_tags("Some patent content")
+
+        assert tags == ["other"]
+
+    def test_classify_handles_malformed_json(self, mocker, mock_database):
+        """Test graceful handling of non-JSON LLM response."""
+        mock_openai = mocker.patch("SPARC.llm.OpenAI")
+        mock_client = Mock()
+        mock_openai.return_value = mock_client
+
+        mock_response = Mock()
+        mock_response.choices = [Mock(message=Mock(content="ai, semiconductors"))]
+        mock_client.chat.completions.create.return_value = mock_response
+
+        analyzer = LLMAnalyzer(api_key="test-key")
+        tags = analyzer.classify_patent_tags("Some patent content")
+
+        assert tags == ["other"]
+
+    def test_classify_handles_api_error(self, mocker, mock_database):
+        """Test graceful fallback when LLM API call fails."""
+        mock_openai = mocker.patch("SPARC.llm.OpenAI")
+        mock_client = Mock()
+        mock_openai.return_value = mock_client
+
+        mock_client.chat.completions.create.side_effect = Exception("API timeout")
+
+        analyzer = LLMAnalyzer(api_key="test-key")
+        tags = analyzer.classify_patent_tags("Some patent content")
+
+        assert tags == ["other"]
+
+    def test_classify_test_mode(self, mocker, mock_database):
+        """Test that test mode returns 'other' without API call."""
+        mocker.patch("SPARC.llm.config")
+
+        analyzer = LLMAnalyzer(test_mode=True)
+        tags = analyzer.classify_patent_tags("Some patent content")
+
+        assert tags == ["other"]
+
+    def test_classify_no_api_client(self, mocker, mock_database):
+        """Test that without API client, classification returns 'other'."""
+        mocker.patch("SPARC.llm.config")
+
+        analyzer = LLMAnalyzer(use_cache=False)
+        tags = analyzer.classify_patent_tags("Some patent content")
+
+        assert tags == ["other"]
+
+    def test_canonical_tags_list(self):
+        """Test that the canonical tag list matches requirements."""
+        expected = ["ai", "semiconductors", "materials", "biotech", "networking", "other"]
+        assert LLMAnalyzer.CANONICAL_TAGS == expected
+
+    def test_classify_uses_model_override(self, mocker, mock_database):
+        """Test that model override is passed to the API call."""
+        mock_openai = mocker.patch("SPARC.llm.OpenAI")
+        mock_client = Mock()
+        mock_openai.return_value = mock_client
+
+        mock_response = Mock()
+        mock_response.choices = [Mock(message=Mock(content='["ai"]'))]
+        mock_client.chat.completions.create.return_value = mock_response
+
+        analyzer = LLMAnalyzer(api_key="test-key")
+        analyzer.classify_patent_tags("content", model="openai/gpt-4o")
+
+        call_args = mock_client.chat.completions.create.call_args
+        assert call_args[1]["model"] == "openai/gpt-4o"
+
+
+class TestPatentTagsStorage:
+    """Test that tags are persisted to the database."""
+
+    @pytest.fixture(autouse=True)
+    def mock_db(self, mocker):
+        """Mock DatabaseClient for all tests."""
+        mock_db_cls = mocker.patch("SPARC.analyzer.DatabaseClient")
+        mock_db_instance = MagicMock()
+        mock_db_instance.get_cached_patent.return_value = None
+        mock_db_instance.get_cached_serp_query.return_value = None
+        mock_db_cls.return_value = mock_db_instance
+        return mock_db_instance
+
+    def test_tags_stored_after_classification(self, mocker, mock_db):
+        """Test that classify_patent_tags results are stored via update_patent_tags."""
+        from SPARC.analyzer import CompanyAnalyzer
+        from SPARC.types import Patent, Patents
+
+        mock_query = mocker.patch("SPARC.analyzer.SERP.query")
+        mock_save = mocker.patch("SPARC.analyzer.SERP.save_patents")
+        mock_parse = mocker.patch("SPARC.analyzer.SERP.parse_patent_pdf")
+        mock_minimize = mocker.patch("SPARC.analyzer.SERP.minimize_patent_for_llm")
+        mock_llm_cls = mocker.patch("SPARC.analyzer.LLMAnalyzer")
+
+        patent = Patent(patent_id="US123", pdf_link="http://example.com/test.pdf")
+        mock_query.return_value = Patents(patents=[patent])
+
+        def save_side_effect(p):
+            p.pdf_path = "patents/US123.pdf"
+            return p
+
+        mock_save.side_effect = save_side_effect
+        mock_parse.return_value = {"abstract": "Test abstract"}
+        mock_minimize.return_value = "Minimized content"
+
+        mock_llm_instance = Mock()
+        mock_llm_instance.analyze_patent_portfolio.return_value = "Analysis result"
+        mock_llm_instance.classify_patent_tags.return_value = ["ai", "semiconductors"]
+        mock_llm_cls.return_value = mock_llm_instance
+
+        analyzer = CompanyAnalyzer()
+        analyzer.analyze_company("TestCorp")
+
+        # Verify classification was called
+        mock_llm_instance.classify_patent_tags.assert_called_once_with(
+            patent_content="Minimized content", model=None
+        )
+
+        # Verify tags were persisted
+        mock_db.update_patent_tags.assert_called_once_with("US123", ["ai", "semiconductors"])
+
+    def test_cached_tags_skip_classification(self, mocker, mock_db):
+        """Test that patents with cached tags skip re-classification."""
+        from SPARC.analyzer import CompanyAnalyzer
+        from SPARC.types import Patent, Patents
+
+        mocker.patch("SPARC.analyzer.SERP.query")
+        mocker.patch("SPARC.analyzer.SERP.save_patents")
+        mock_llm_cls = mocker.patch("SPARC.analyzer.LLMAnalyzer")
+
+        # Simulate DB cache hit with tags
+        mock_db.get_cached_patent.return_value = {
+            "patent_id": "US123",
+            "minimized_content": "Cached content",
+            "patent_tags": ["biotech"],
+        }
+        mock_db.get_cached_serp_query.return_value = ["US123"]
+
+        mock_llm_instance = Mock()
+        mock_llm_instance.analyze_patent_portfolio.return_value = "Analysis"
+        mock_llm_cls.return_value = mock_llm_instance
+
+        analyzer = CompanyAnalyzer()
+        analyzer.analyze_company("TestCorp")
+
+        # Should NOT classify since tags already present from cache
+        mock_llm_instance.classify_patent_tags.assert_not_called()
+        mock_db.update_patent_tags.assert_not_called()
+
+    def test_tags_in_analysis_result(self, mocker, mock_db):
+        """Test that tags appear in the CompanyAnalysisResult."""
+        from SPARC.analyzer import CompanyAnalyzer
+        from SPARC.types import Patent, Patents
+
+        mock_query = mocker.patch("SPARC.analyzer.SERP.query")
+        mock_save = mocker.patch("SPARC.analyzer.SERP.save_patents")
+        mock_parse = mocker.patch("SPARC.analyzer.SERP.parse_patent_pdf")
+        mock_minimize = mocker.patch("SPARC.analyzer.SERP.minimize_patent_for_llm")
+        mock_llm_cls = mocker.patch("SPARC.analyzer.LLMAnalyzer")
+
+        patent = Patent(patent_id="US123", pdf_link="http://example.com/test.pdf")
+        mock_query.return_value = Patents(patents=[patent])
+
+        def save_side_effect(p):
+            p.pdf_path = "patents/US123.pdf"
+            return p
+
+        mock_save.side_effect = save_side_effect
+        mock_parse.return_value = {"abstract": "Test abstract"}
+        mock_minimize.return_value = "Minimized content"
+
+        mock_llm_instance = Mock()
+        mock_llm_instance.analyze_patent_portfolio.return_value = "Strong innovation"
+        mock_llm_instance.classify_patent_tags.return_value = ["ai", "networking"]
+        mock_llm_cls.return_value = mock_llm_instance
+
+        # After analysis, get_cached_patent returns the patent with tags
+        mock_db.get_cached_serp_query.side_effect = [None, ["US123"]]
+        mock_db.get_cached_patent.side_effect = [
+            None,  # First call during _process_single_patent
+            {"patent_id": "US123", "patent_tags": ["ai", "networking"]},  # Second call during _analyze_company_safe
+        ]
+
+        analyzer = CompanyAnalyzer()
+        result = analyzer._analyze_company_safe("TestCorp")
+
+        assert result.success is True
+        assert result.tags == ["ai", "networking"]

tests/test_rate_limit_admin.py

@@ -0,0 +1,109 @@
+"""Tests for the /admin/rate-limits endpoint."""
+
+from unittest.mock import patch
+
+import pytest
+from fastapi.testclient import TestClient
+
+from SPARC import api
+from SPARC.api import app
+from SPARC.auth import UserResponse
+
+
+@pytest.fixture
+def client():
+    """Create test client."""
+    return TestClient(app)
+
+
+@pytest.fixture(autouse=True)
+def reset_stats():
+    """Reset rate limit stats between tests."""
+    api._rate_limit_stats.clear()
+    yield
+    api._rate_limit_stats.clear()
+
+
+def _mock_admin():
+    """Return a mock admin user."""
+    return UserResponse(id=1, email="admin@test.com", role="admin", created_at="2025-01-01T00:00:00")
+
+
+def _mock_user():
+    """Return a mock non-admin user."""
+    return UserResponse(id=2, email="user@test.com", role="user", created_at="2025-01-01T00:00:00")
+
+
+class TestRateLimitAdminEndpoint:
+    """Test GET /admin/rate-limits."""
+
+    def test_admin_can_access(self, client):
+        """Admin users should be able to access the rate-limits endpoint."""
+        app.dependency_overrides[api.get_current_admin] = _mock_admin
+        try:
+            response = client.get("/admin/rate-limits")
+            assert response.status_code == 200
+            data = response.json()
+            assert "rate_limits" in data
+            assert isinstance(data["rate_limits"], list)
+        finally:
+            app.dependency_overrides.clear()
+
+    def test_non_admin_rejected(self, client):
+        """Non-admin users should get 403."""
+        # Without overriding the dependency, it should fail auth
+        response = client.get("/admin/rate-limits")
+        assert response.status_code in (401, 403)
+
+    def test_returns_configured_endpoints(self, client):
+        """Should list all rate-limited endpoints."""
+        app.dependency_overrides[api.get_current_admin] = _mock_admin
+        try:
+            response = client.get("/admin/rate-limits")
+            assert response.status_code == 200
+            data = response.json()
+            endpoints = [rl["endpoint"] for rl in data["rate_limits"]]
+            assert "/auth/register" in endpoints
+            assert "/auth/login" in endpoints
+        finally:
+            app.dependency_overrides.clear()
+
+    def test_empty_state_shows_zero_counts(self, client):
+        """When no requests have been made, counts should be zero."""
+        app.dependency_overrides[api.get_current_admin] = _mock_admin
+        try:
+            response = client.get("/admin/rate-limits")
+            data = response.json()
+            for rl in data["rate_limits"]:
+                assert rl["total_requests"] == 0
+                assert rl["rejected_requests"] == 0
+        finally:
+            app.dependency_overrides.clear()
+
+    def test_tracks_requests(self, client):
+        """After making requests, the stats should reflect them."""
+        api._track_rate_limit_request("/auth/login", "127.0.0.1")
+        api._track_rate_limit_request("/auth/login", "127.0.0.1")
+        api._track_rate_limit_request("/auth/login", "192.168.1.1", rejected=True)
+
+        app.dependency_overrides[api.get_current_admin] = _mock_admin
+        try:
+            response = client.get("/admin/rate-limits")
+            data = response.json()
+            login_stats = next(rl for rl in data["rate_limits"] if rl["endpoint"] == "/auth/login")
+            assert login_stats["total_requests"] == 3
+            assert login_stats["rejected_requests"] == 1
+        finally:
+            app.dependency_overrides.clear()
+
+    def test_includes_limit_config(self, client):
+        """Each endpoint entry should include the rate limit config string."""
+        app.dependency_overrides[api.get_current_admin] = _mock_admin
+        try:
+            response = client.get("/admin/rate-limits")
+            data = response.json()
+            for rl in data["rate_limits"]:
+                assert "limit" in rl
+                assert isinstance(rl["limit"], str)
+        finally:
+            app.dependency_overrides.clear()

tests/test_storage.py

@@ -0,0 +1,263 @@
+"""Tests for S3/MinIO storage backend in storage.py.
+
+Covers issue #1660:
+- S3StorageBackend read, write, exists, path_for
+- Error handling: NoSuchKey, generic S3 errors, bucket auto-creation
+- get_storage_backend() factory function
+- LocalStorageBackend (basic sanity checks)
+"""
+
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from SPARC.storage import LocalStorageBackend, S3StorageBackend, get_storage_backend
+
+
+# ---------- S3StorageBackend ----------
+
+class TestS3StorageBackend:
+    """Tests for the S3-compatible storage backend."""
+
+    @pytest.fixture
+    def s3_backend(self):
+        """Create an S3StorageBackend with a fully mocked boto3 client."""
+        with patch.dict("sys.modules", {"boto3": MagicMock()}):
+            import boto3 as mock_boto
+            mock_s3 = MagicMock()
+            mock_boto.client.return_value = mock_s3
+            mock_s3.head_bucket.return_value = {}
+
+            backend = S3StorageBackend(
+                bucket="test-bucket",
+                endpoint_url="http://minio:9000",
+                access_key="minioadmin",
+                secret_key="minioadmin",
+            )
+            # Expose mock for assertions
+            backend._mock_s3 = mock_s3
+            yield backend
+
+    def test_write_puts_object(self, s3_backend):
+        """write() calls put_object with correct bucket, key, and body."""
+        s3_backend.write("US-12345678-B2.pdf", b"PDF content here")
+
+        s3_backend._mock_s3.put_object.assert_called_once_with(
+            Bucket="test-bucket",
+            Key="US-12345678-B2.pdf",
+            Body=b"PDF content here",
+            ContentType="application/pdf",
+        )
+
+    def test_read_returns_body(self, s3_backend):
+        """read() returns the Body content from get_object."""
+        mock_body = MagicMock()
+        mock_body.read.return_value = b"PDF data"
+        s3_backend._mock_s3.get_object.return_value = {"Body": mock_body}
+
+        result = s3_backend.read("US-12345678-B2.pdf")
+
+        assert result == b"PDF data"
+        s3_backend._mock_s3.get_object.assert_called_once_with(
+            Bucket="test-bucket",
+            Key="US-12345678-B2.pdf",
+        )
+
+    def test_read_nosuchkey_raises_file_not_found(self, s3_backend):
+        """read() raises FileNotFoundError when object does not exist."""
+        # Create a NoSuchKey exception class on the mock
+        nosuchkey = type("NoSuchKey", (Exception,), {})
+        s3_backend._mock_s3.exceptions.NoSuchKey = nosuchkey
+        s3_backend._mock_s3.get_object.side_effect = nosuchkey("not found")
+
+        # Reassign s3 to trigger the except branch
+        s3_backend.s3 = s3_backend._mock_s3
+
+        with pytest.raises(FileNotFoundError, match="S3 object not found"):
+            s3_backend.read("missing.pdf")
+
+    def test_read_generic_404_raises_file_not_found(self, s3_backend):
+        """read() handles generic 404 errors from S3-compatible APIs."""
+        nosuchkey = type("NoSuchKey", (Exception,), {})
+        s3_backend._mock_s3.exceptions.NoSuchKey = nosuchkey
+        s3_backend.s3 = s3_backend._mock_s3
+        s3_backend.s3.get_object.side_effect = Exception("An error occurred (404)")
+
+        with pytest.raises(FileNotFoundError, match="S3 object not found"):
+            s3_backend.read("missing.pdf")
+
+    def test_read_other_error_re_raises(self, s3_backend):
+        """read() re-raises non-404 errors."""
+        nosuchkey = type("NoSuchKey", (Exception,), {})
+        s3_backend._mock_s3.exceptions.NoSuchKey = nosuchkey
+        s3_backend.s3 = s3_backend._mock_s3
+        s3_backend.s3.get_object.side_effect = Exception("Internal server error")
+
+        with pytest.raises(Exception, match="Internal server error"):
+            s3_backend.read("some-file.pdf")
+
+    def test_exists_returns_true_for_existing_object(self, s3_backend):
+        """exists() returns True when head_object succeeds with content."""
+        s3_backend._mock_s3.head_object.return_value = {"ContentLength": 1024}
+
+        assert s3_backend.exists("US-12345678-B2.pdf") is True
+
+    def test_exists_returns_false_for_missing_object(self, s3_backend):
+        """exists() returns False when head_object raises an exception."""
+        s3_backend._mock_s3.head_object.side_effect = Exception("Not Found")
+
+        assert s3_backend.exists("missing.pdf") is False
+
+    def test_exists_returns_false_for_zero_length(self, s3_backend):
+        """exists() returns False when object has zero content length."""
+        s3_backend._mock_s3.head_object.return_value = {"ContentLength": 0}
+
+        assert s3_backend.exists("empty.pdf") is False
+
+    def test_path_for_returns_s3_uri(self, s3_backend):
+        """path_for() returns an s3:// URI."""
+        path = s3_backend.path_for("US-12345678-B2.pdf")
+
+        assert path == "s3://test-bucket/US-12345678-B2.pdf"
+
+    def test_constructor_creates_bucket_if_missing(self):
+        """Constructor creates the bucket if head_bucket fails."""
+        with patch.dict("sys.modules", {"boto3": MagicMock()}):
+            import boto3 as mock_boto
+            mock_s3 = MagicMock()
+            mock_boto.client.return_value = mock_s3
+            mock_s3.head_bucket.side_effect = Exception("Bucket not found")
+
+            S3StorageBackend(
+                bucket="new-bucket",
+                endpoint_url="http://minio:9000",
+                access_key="admin",
+                secret_key="admin",
+            )
+
+            mock_s3.create_bucket.assert_called_once_with(Bucket="new-bucket")
+
+    def test_constructor_handles_bucket_creation_failure(self):
+        """Constructor logs warning but does not crash if bucket creation fails."""
+        with patch.dict("sys.modules", {"boto3": MagicMock()}):
+            import boto3 as mock_boto
+            mock_s3 = MagicMock()
+            mock_boto.client.return_value = mock_s3
+            mock_s3.head_bucket.side_effect = Exception("Bucket not found")
+            mock_s3.create_bucket.side_effect = Exception("Permission denied")
+
+            # Should not raise
+            backend = S3StorageBackend(
+                bucket="locked-bucket",
+                endpoint_url="http://minio:9000",
+                access_key="admin",
+                secret_key="admin",
+            )
+            assert backend.bucket == "locked-bucket"
+
+    def test_constructor_passes_endpoint_and_credentials(self):
+        """Constructor passes endpoint_url and credentials to boto3.client."""
+        with patch.dict("sys.modules", {"boto3": MagicMock()}):
+            import boto3 as mock_boto
+            mock_s3 = MagicMock()
+            mock_boto.client.return_value = mock_s3
+
+            S3StorageBackend(
+                bucket="test",
+                endpoint_url="http://minio:9000",
+                access_key="mykey",
+                secret_key="mysecret",
+            )
+
+            mock_boto.client.assert_called_with(
+                "s3",
+                endpoint_url="http://minio:9000",
+                aws_access_key_id="mykey",
+                aws_secret_access_key="mysecret",
+            )
+
+
+# ---------- LocalStorageBackend ----------
+
+class TestLocalStorageBackend:
+    """Basic sanity checks for the local filesystem backend."""
+
+    def test_write_and_read(self, tmp_path):
+        """Write and read round-trip produces identical content."""
+        backend = LocalStorageBackend(base_dir=str(tmp_path))
+        backend.write("test.pdf", b"hello world")
+
+        result = backend.read("test.pdf")
+        assert result == b"hello world"
+
+    def test_read_missing_file_raises(self, tmp_path):
+        """Reading a non-existent file raises FileNotFoundError."""
+        backend = LocalStorageBackend(base_dir=str(tmp_path))
+
+        with pytest.raises(FileNotFoundError):
+            backend.read("nonexistent.pdf")
+
+    def test_exists_true_for_written_file(self, tmp_path):
+        """exists() returns True after writing a file."""
+        backend = LocalStorageBackend(base_dir=str(tmp_path))
+        backend.write("test.pdf", b"data")
+
+        assert backend.exists("test.pdf") is True
+
+    def test_exists_false_for_missing_file(self, tmp_path):
+        """exists() returns False for non-existent file."""
+        backend = LocalStorageBackend(base_dir=str(tmp_path))
+
+        assert backend.exists("missing.pdf") is False
+
+    def test_exists_false_for_empty_file(self, tmp_path):
+        """exists() returns False for zero-length file."""
+        backend = LocalStorageBackend(base_dir=str(tmp_path))
+        backend.write("empty.pdf", b"")
+
+        assert backend.exists("empty.pdf") is False
+
+    def test_path_for_returns_full_path(self, tmp_path):
+        """path_for() returns the full filesystem path."""
+        backend = LocalStorageBackend(base_dir=str(tmp_path))
+        path = backend.path_for("test.pdf")
+
+        assert path == str(tmp_path / "test.pdf")
+
+
+# ---------- get_storage_backend() factory ----------
+
+class TestGetStorageBackend:
+    """Tests for the storage backend factory function."""
+
+    @patch("SPARC.storage.config")
+    def test_returns_local_backend_by_default(self, mock_config):
+        """Default config returns LocalStorageBackend."""
+        mock_config.storage_backend = "local"
+
+        backend = get_storage_backend()
+
+        assert isinstance(backend, LocalStorageBackend)
+
+    @patch("SPARC.storage.config")
+    def test_returns_s3_backend_when_configured(self, mock_config):
+        """Setting storage_backend=s3 returns S3StorageBackend."""
+        mock_config.storage_backend = "s3"
+        mock_config.s3_bucket = "test-bucket"
+        mock_config.s3_endpoint_url = "http://minio:9000"
+        mock_config.s3_access_key = "key"
+        mock_config.s3_secret_key = "secret"
+
+        with patch.dict("sys.modules", {"boto3": MagicMock()}):
+            backend = get_storage_backend()
+
+        assert isinstance(backend, S3StorageBackend)
+
+    @patch("SPARC.storage.config")
+    def test_case_insensitive_backend_selection(self, mock_config):
+        """Backend selection is case-insensitive."""
+        mock_config.storage_backend = "LOCAL"
+
+        backend = get_storage_backend()
+
+        assert isinstance(backend, LocalStorageBackend)

tests/test_tracked_companies.py

@@ -0,0 +1,387 @@
+"""Tests for tracked company admin endpoints and scheduler integration.
+
+Covers issue #1656:
+- GET /admin/tracked (list tracked companies)
+- POST /admin/tracked (add a tracked company)
+- DELETE /admin/tracked/{company_name} (remove a tracked company)
+- GET /admin/alerts (list alerts)
+- scheduler.run_scheduled_analysis() integration
+
+All tests mock the database layer and use JWT auth fixtures.
+"""
+
+from datetime import datetime, timezone
+from unittest.mock import MagicMock, patch, call
+
+import pytest
+from fastapi.testclient import TestClient
+
+from SPARC.api import app
+from SPARC.auth import create_access_token
+
+
+@pytest.fixture
+def client():
+    """Create test client."""
+    return TestClient(app)
+
+
+@pytest.fixture(autouse=True)
+def mock_db():
+    """Mock the database client used by admin and auth endpoints."""
+    db = MagicMock()
+
+    # Default admin user for auth
+    db.get_user_by_id.return_value = {
+        "id": 1,
+        "email": "admin@test.com",
+        "role": "admin",
+        "created_at": datetime(2025, 1, 1, tzinfo=timezone.utc),
+    }
+
+    with patch("SPARC.api.get_db_client", return_value=db), \
+         patch("SPARC.auth.get_db_client", return_value=db):
+        yield db
+
+
+def _admin_header():
+    """Create an Authorization header with a valid admin access token."""
+    token = create_access_token(1, "admin@test.com", "admin")
+    return {"Authorization": f"Bearer {token}"}
+
+
+def _user_header():
+    """Create an Authorization header with a regular user access token."""
+    token = create_access_token(2, "user@test.com", "user")
+    return {"Authorization": f"Bearer {token}"}
+
+
+# ---------- GET /admin/tracked ----------
+
+class TestListTrackedCompanies:
+    """GET /admin/tracked"""
+
+    def test_list_tracked_returns_companies(self, client, mock_db):
+        """Admin can list tracked companies."""
+        mock_db.list_tracked_companies.return_value = [
+            {"company_name": "NVIDIA", "last_patent_count": 120, "last_analyzed": "2025-06-15"},
+            {"company_name": "AMD", "last_patent_count": 80, "last_analyzed": "2025-06-14"},
+        ]
+
+        response = client.get("/admin/tracked", headers=_admin_header())
+
+        assert response.status_code == 200
+        data = response.json()
+        assert len(data) == 2
+        assert data[0]["company_name"] == "NVIDIA"
+
+    def test_list_tracked_empty(self, client, mock_db):
+        """Returns empty list when no companies are tracked."""
+        mock_db.list_tracked_companies.return_value = []
+
+        response = client.get("/admin/tracked", headers=_admin_header())
+
+        assert response.status_code == 200
+        assert response.json() == []
+
+    def test_list_tracked_requires_admin(self, client, mock_db):
+        """Regular user cannot access tracked companies list."""
+        mock_db.get_user_by_id.return_value = {
+            "id": 2,
+            "email": "user@test.com",
+            "role": "user",
+            "created_at": datetime(2025, 1, 1, tzinfo=timezone.utc),
+        }
+
+        response = client.get("/admin/tracked", headers=_user_header())
+
+        assert response.status_code == 403
+
+    def test_list_tracked_unauthenticated(self, client):
+        """Unauthenticated request returns 401."""
+        response = client.get("/admin/tracked")
+        assert response.status_code == 401
+
+
+# ---------- POST /admin/tracked ----------
+
+class TestAddTrackedCompany:
+    """POST /admin/tracked"""
+
+    def test_add_tracked_company_success(self, client, mock_db):
+        """Admin can add a company to tracking."""
+        mock_db.add_tracked_company.return_value = {
+            "company_name": "Intel",
+            "last_patent_count": 0,
+            "last_analyzed": None,
+        }
+
+        response = client.post(
+            "/admin/tracked",
+            json={"company_name": "Intel"},
+            headers=_admin_header(),
+        )
+
+        assert response.status_code == 200
+        data = response.json()
+        assert data["company_name"] == "Intel"
+        mock_db.add_tracked_company.assert_called_once_with("Intel")
+
+    def test_add_duplicate_returns_409(self, client, mock_db):
+        """Adding an already-tracked company returns 409."""
+        mock_db.add_tracked_company.return_value = None
+
+        response = client.post(
+            "/admin/tracked",
+            json={"company_name": "NVIDIA"},
+            headers=_admin_header(),
+        )
+
+        assert response.status_code == 409
+        assert "already tracked" in response.json()["detail"].lower()
+
+    def test_add_tracked_requires_admin(self, client, mock_db):
+        """Regular user cannot add tracked companies."""
+        mock_db.get_user_by_id.return_value = {
+            "id": 2,
+            "email": "user@test.com",
+            "role": "user",
+            "created_at": datetime(2025, 1, 1, tzinfo=timezone.utc),
+        }
+
+        response = client.post(
+            "/admin/tracked",
+            json={"company_name": "Intel"},
+            headers=_user_header(),
+        )
+
+        assert response.status_code == 403
+
+    def test_add_tracked_empty_name_rejected(self, client):
+        """Empty company name is rejected by validation."""
+        response = client.post(
+            "/admin/tracked",
+            json={"company_name": ""},
+            headers=_admin_header(),
+        )
+
+        assert response.status_code == 422  # Pydantic validation error
+
+
+# ---------- DELETE /admin/tracked/{company_name} ----------
+
+class TestRemoveTrackedCompany:
+    """DELETE /admin/tracked/{company_name}"""
+
+    def test_remove_tracked_company_success(self, client, mock_db):
+        """Admin can remove a tracked company."""
+        mock_db.remove_tracked_company.return_value = True
+
+        response = client.delete(
+            "/admin/tracked/NVIDIA",
+            headers=_admin_header(),
+        )
+
+        assert response.status_code == 200
+        assert "Stopped tracking" in response.json()["message"]
+        mock_db.remove_tracked_company.assert_called_once_with("NVIDIA")
+
+    def test_remove_nonexistent_returns_404(self, client, mock_db):
+        """Removing a non-tracked company returns 404."""
+        mock_db.remove_tracked_company.return_value = False
+
+        response = client.delete(
+            "/admin/tracked/UnknownCorp",
+            headers=_admin_header(),
+        )
+
+        assert response.status_code == 404
+        assert "not found" in response.json()["detail"].lower()
+
+    def test_remove_tracked_requires_admin(self, client, mock_db):
+        """Regular user cannot remove tracked companies."""
+        mock_db.get_user_by_id.return_value = {
+            "id": 2,
+            "email": "user@test.com",
+            "role": "user",
+            "created_at": datetime(2025, 1, 1, tzinfo=timezone.utc),
+        }
+
+        response = client.delete(
+            "/admin/tracked/NVIDIA",
+            headers=_user_header(),
+        )
+
+        assert response.status_code == 403
+
+
+# ---------- GET /admin/alerts ----------
+
+class TestListAlerts:
+    """GET /admin/alerts"""
+
+    def test_list_alerts_returns_data(self, client, mock_db):
+        """Admin can list alerts."""
+        mock_db.list_alerts.return_value = [
+            {
+                "id": 1,
+                "company_name": "NVIDIA",
+                "alert_type": "patent_count_change",
+                "message": "Patent count increased by 25%",
+                "created_at": "2025-06-15T10:00:00Z",
+            },
+        ]
+
+        response = client.get("/admin/alerts", headers=_admin_header())
+
+        assert response.status_code == 200
+        data = response.json()
+        assert len(data) == 1
+        assert data[0]["alert_type"] == "patent_count_change"
+
+    def test_list_alerts_with_limit(self, client, mock_db):
+        """Custom limit parameter is passed to the database."""
+        mock_db.list_alerts.return_value = []
+
+        response = client.get("/admin/alerts?limit=10", headers=_admin_header())
+
+        assert response.status_code == 200
+        mock_db.list_alerts.assert_called_once_with(limit=10)
+
+    def test_list_alerts_requires_admin(self, client, mock_db):
+        """Regular user cannot access alerts."""
+        mock_db.get_user_by_id.return_value = {
+            "id": 2,
+            "email": "user@test.com",
+            "role": "user",
+            "created_at": datetime(2025, 1, 1, tzinfo=timezone.utc),
+        }
+
+        response = client.get("/admin/alerts", headers=_user_header())
+
+        assert response.status_code == 403
+
+
+# ---------- Scheduler integration ----------
+
+class TestSchedulerIntegration:
+    """Tests for scheduler.run_scheduled_analysis()."""
+
+    def test_no_tracked_companies_skips_analysis(self):
+        """Scheduler does nothing when no companies are tracked."""
+        mock_db = MagicMock()
+        mock_db.list_tracked_companies.return_value = []
+
+        with patch("SPARC.scheduler.get_db_client", return_value=mock_db), \
+             patch("SPARC.scheduler.CompanyAnalyzer") as mock_analyzer_cls:
+            from SPARC.scheduler import run_scheduled_analysis
+            run_scheduled_analysis()
+
+        mock_analyzer_cls.assert_not_called()
+
+    def test_scheduler_analyzes_each_tracked_company(self):
+        """Scheduler runs analysis for every tracked company."""
+        mock_db = MagicMock()
+        mock_db.list_tracked_companies.return_value = [
+            {"company_name": "NVIDIA", "last_patent_count": 100},
+            {"company_name": "AMD", "last_patent_count": 50},
+        ]
+
+        mock_result_nvidia = MagicMock(success=True, patent_count=110)
+        mock_result_amd = MagicMock(success=True, patent_count=55)
+        mock_analyzer = MagicMock()
+        mock_analyzer._analyze_company_safe.side_effect = [mock_result_nvidia, mock_result_amd]
+
+        with patch("SPARC.scheduler.get_db_client", return_value=mock_db), \
+             patch("SPARC.scheduler.CompanyAnalyzer", return_value=mock_analyzer):
+            from SPARC.scheduler import run_scheduled_analysis
+            run_scheduled_analysis()
+
+        assert mock_analyzer._analyze_company_safe.call_count == 2
+        mock_db.update_tracked_company.assert_any_call("NVIDIA", 110)
+        mock_db.update_tracked_company.assert_any_call("AMD", 55)
+
+    def test_scheduler_triggers_alert_on_significant_change(self):
+        """Scheduler stores an alert when patent count changes significantly."""
+        mock_db = MagicMock()
+        mock_db.list_tracked_companies.return_value = [
+            {"company_name": "Tesla", "last_patent_count": 100},
+        ]
+
+        mock_result = MagicMock(success=True, patent_count=130)  # 30% increase
+        mock_analyzer = MagicMock()
+        mock_analyzer._analyze_company_safe.return_value = mock_result
+
+        with patch("SPARC.scheduler.get_db_client", return_value=mock_db), \
+             patch("SPARC.scheduler.CompanyAnalyzer", return_value=mock_analyzer):
+            from SPARC.scheduler import run_scheduled_analysis
+            run_scheduled_analysis()
+
+        mock_db.store_alert.assert_called_once()
+        alert_kwargs = mock_db.store_alert.call_args
+        assert alert_kwargs[1]["company_name"] == "Tesla"
+        assert alert_kwargs[1]["alert_type"] == "patent_count_change"
+        assert alert_kwargs[1]["old_value"] == 100
+        assert alert_kwargs[1]["new_value"] == 130
+
+    def test_scheduler_no_alert_for_small_change(self):
+        """Scheduler does not alert when change is below threshold."""
+        mock_db = MagicMock()
+        mock_db.list_tracked_companies.return_value = [
+            {"company_name": "Intel", "last_patent_count": 100},
+        ]
+
+        mock_result = MagicMock(success=True, patent_count=105)  # 5% increase
+        mock_analyzer = MagicMock()
+        mock_analyzer._analyze_company_safe.return_value = mock_result
+
+        with patch("SPARC.scheduler.get_db_client", return_value=mock_db), \
+             patch("SPARC.scheduler.CompanyAnalyzer", return_value=mock_analyzer):
+            from SPARC.scheduler import run_scheduled_analysis
+            run_scheduled_analysis()
+
+        mock_db.store_alert.assert_not_called()
+
+    def test_scheduler_handles_analysis_failure(self):
+        """Scheduler continues when one company fails analysis."""
+        mock_db = MagicMock()
+        mock_db.list_tracked_companies.return_value = [
+            {"company_name": "FailCo", "last_patent_count": 50},
+            {"company_name": "SuccessCo", "last_patent_count": 30},
+        ]
+
+        mock_fail_result = MagicMock(success=False, error="API timeout")
+        mock_ok_result = MagicMock(success=True, patent_count=35)
+        mock_analyzer = MagicMock()
+        mock_analyzer._analyze_company_safe.side_effect = [mock_fail_result, mock_ok_result]
+
+        with patch("SPARC.scheduler.get_db_client", return_value=mock_db), \
+             patch("SPARC.scheduler.CompanyAnalyzer", return_value=mock_analyzer):
+            from SPARC.scheduler import run_scheduled_analysis
+            run_scheduled_analysis()
+
+        # FailCo should not get updated, SuccessCo should
+        mock_db.update_tracked_company.assert_called_once_with("SuccessCo", 35)
+
+    def test_scheduler_handles_exception_in_analysis(self):
+        """Scheduler continues even when analysis raises an exception."""
+        mock_db = MagicMock()
+        mock_db.list_tracked_companies.return_value = [
+            {"company_name": "CrashCo", "last_patent_count": 10},
+            {"company_name": "OKCo", "last_patent_count": 20},
+        ]
+
+        mock_ok_result = MagicMock(success=True, patent_count=22)
+        mock_analyzer = MagicMock()
+        mock_analyzer._analyze_company_safe.side_effect = [
+            RuntimeError("unexpected error"),
+            mock_ok_result,
+        ]
+
+        with patch("SPARC.scheduler.get_db_client", return_value=mock_db), \
+             patch("SPARC.scheduler.CompanyAnalyzer", return_value=mock_analyzer):
+            from SPARC.scheduler import run_scheduled_analysis
+            run_scheduled_analysis()
+
+        # OKCo should still be processed
+        mock_db.update_tracked_company.assert_called_once_with("OKCo", 22)

tests/test_webhooks.py

@@ -0,0 +1,280 @@
+"""Tests for webhook notification system: retry logic and Slack/Discord payload format.
+
+Covers issue #1657:
+- Retry logic with exponential backoff in _send_with_retry
+- Slack/Discord payload formatting in _build_payload
+- Generic HTTP POST payload formatting
+- notify() dispatching to multiple URLs
+- notify_job_completed() and notify_alert() convenience helpers
+"""
+
+from datetime import datetime
+from unittest.mock import MagicMock, patch, call
+
+import pytest
+import requests
+
+from SPARC.webhooks import (
+    MAX_RETRIES,
+    _build_payload,
+    _is_slack_url,
+    _send_with_retry,
+    notify,
+    notify_alert,
+    notify_job_completed,
+)
+
+
+class TestIsSlackUrl:
+    """Tests for Slack/Discord URL detection."""
+
+    def test_slack_webhook_url(self):
+        assert _is_slack_url("https://hooks.slack.com/services/T00/B00/xxx") is True
+
+    def test_discord_webhook_url(self):
+        assert _is_slack_url("https://discord.com/api/webhooks/123/abc") is True
+
+    def test_generic_url(self):
+        assert _is_slack_url("https://example.com/webhook") is False
+
+    def test_empty_url(self):
+        assert _is_slack_url("") is False
+
+
+class TestBuildPayload:
+    """Tests for payload construction."""
+
+    def test_generic_payload_structure(self):
+        """Generic payload includes event type, timestamp, and data."""
+        payload = _build_payload("job_completed", {"job_id": "abc123"})
+
+        assert payload["event"] == "job_completed"
+        assert payload["job_id"] == "abc123"
+        assert "timestamp" in payload
+        # Timestamp should be ISO format ending with Z
+        assert payload["timestamp"].endswith("Z")
+
+    def test_slack_payload_wraps_in_text(self):
+        """Slack payload wraps content in a 'text' field."""
+        payload = _build_payload("patent_alert", {"company_name": "NVIDIA"}, slack=True)
+
+        assert "text" in payload
+        assert "patent_alert" in payload["text"]
+        assert "NVIDIA" in payload["text"]
+        # Slack payload should NOT have the event/timestamp at top level
+        assert "event" not in payload
+        assert "timestamp" not in payload
+
+    def test_generic_payload_does_not_have_text_field(self):
+        """Non-Slack payload does not wrap in text."""
+        payload = _build_payload("job_completed", {"status": "done"})
+
+        assert "text" not in payload
+        assert payload["status"] == "done"
+
+    def test_slack_payload_contains_bold_header(self):
+        """Slack payload starts with bold event header using Slack markdown."""
+        payload = _build_payload("job_completed", {"count": 5}, slack=True)
+
+        assert payload["text"].startswith("*[SPARC] job_completed*")
+
+    def test_payload_merges_all_data_keys(self):
+        """All data keys are included in the generic payload."""
+        data = {"key1": "val1", "key2": 42, "key3": True}
+        payload = _build_payload("test_event", data)
+
+        assert payload["key1"] == "val1"
+        assert payload["key2"] == 42
+        assert payload["key3"] is True
+
+
+class TestSendWithRetry:
+    """Tests for retry logic in _send_with_retry."""
+
+    @patch("SPARC.webhooks.time.sleep")
+    @patch("SPARC.webhooks.requests.post")
+    def test_success_on_first_attempt(self, mock_post, mock_sleep):
+        """Successful delivery on first attempt, no retries."""
+        mock_post.return_value = MagicMock(status_code=200)
+
+        result = _send_with_retry("https://example.com/hook", {"event": "test"})
+
+        assert result is True
+        mock_post.assert_called_once()
+        mock_sleep.assert_not_called()
+
+    @patch("SPARC.webhooks.time.sleep")
+    @patch("SPARC.webhooks.requests.post")
+    def test_success_on_second_attempt(self, mock_post, mock_sleep):
+        """Fails first, succeeds on retry."""
+        mock_post.side_effect = [
+            MagicMock(status_code=500),
+            MagicMock(status_code=200),
+        ]
+
+        result = _send_with_retry("https://example.com/hook", {"event": "test"})
+
+        assert result is True
+        assert mock_post.call_count == 2
+        mock_sleep.assert_called_once()
+
+    @patch("SPARC.webhooks.time.sleep")
+    @patch("SPARC.webhooks.requests.post")
+    def test_all_retries_exhausted(self, mock_post, mock_sleep):
+        """Returns False after all retries fail."""
+        mock_post.return_value = MagicMock(status_code=500)
+
+        result = _send_with_retry("https://example.com/hook", {"event": "test"})
+
+        assert result is False
+        assert mock_post.call_count == MAX_RETRIES
+        assert mock_sleep.call_count == MAX_RETRIES - 1
+
+    @patch("SPARC.webhooks.time.sleep")
+    @patch("SPARC.webhooks.requests.post")
+    def test_exponential_backoff_timing(self, mock_post, mock_sleep):
+        """Backoff wait times follow exponential pattern (2^attempt)."""
+        mock_post.return_value = MagicMock(status_code=500)
+
+        _send_with_retry("https://example.com/hook", {"event": "test"})
+
+        # With BACKOFF_BASE=2: attempt 1 -> sleep(2), attempt 2 -> sleep(4)
+        expected_waits = [call(2 ** i) for i in range(1, MAX_RETRIES)]
+        assert mock_sleep.call_args_list == expected_waits
+
+    @patch("SPARC.webhooks.time.sleep")
+    @patch("SPARC.webhooks.requests.post")
+    def test_network_error_triggers_retry(self, mock_post, mock_sleep):
+        """Network exceptions trigger retry, not immediate failure."""
+        mock_post.side_effect = [
+            requests.ConnectionError("Connection refused"),
+            MagicMock(status_code=200),
+        ]
+
+        result = _send_with_retry("https://example.com/hook", {"event": "test"})
+
+        assert result is True
+        assert mock_post.call_count == 2
+
+    @patch("SPARC.webhooks.time.sleep")
+    @patch("SPARC.webhooks.requests.post")
+    def test_timeout_error_triggers_retry(self, mock_post, mock_sleep):
+        """Timeout exceptions trigger retry."""
+        mock_post.side_effect = [
+            requests.Timeout("Request timed out"),
+            MagicMock(status_code=200),
+        ]
+
+        result = _send_with_retry("https://example.com/hook", {"event": "test"})
+
+        assert result is True
+        assert mock_post.call_count == 2
+
+    @patch("SPARC.webhooks.time.sleep")
+    @patch("SPARC.webhooks.requests.post")
+    def test_2xx_status_codes_accepted(self, mock_post, mock_sleep):
+        """Any 2xx status code is treated as success."""
+        mock_post.return_value = MagicMock(status_code=204)
+
+        result = _send_with_retry("https://example.com/hook", {"event": "test"})
+
+        assert result is True
+        mock_post.assert_called_once()
+
+    @patch("SPARC.webhooks.time.sleep")
+    @patch("SPARC.webhooks.requests.post")
+    def test_posts_json_payload(self, mock_post, mock_sleep):
+        """Payload is sent as JSON with correct timeout."""
+        mock_post.return_value = MagicMock(status_code=200)
+        payload = {"event": "test", "data": "value"}
+
+        _send_with_retry("https://example.com/hook", payload)
+
+        mock_post.assert_called_once_with(
+            "https://example.com/hook", json=payload, timeout=10
+        )
+
+
+class TestNotify:
+    """Tests for the notify() dispatcher."""
+
+    @patch("SPARC.webhooks._send_with_retry")
+    @patch("SPARC.webhooks.WEBHOOK_URLS", ["https://example.com/hook1", "https://example.com/hook2"])
+    def test_dispatches_to_all_urls(self, mock_send):
+        """notify() sends to every configured webhook URL."""
+        mock_send.return_value = True
+
+        notify("job_completed", {"job_id": "test123"})
+
+        assert mock_send.call_count == 2
+
+    @patch("SPARC.webhooks._send_with_retry")
+    @patch("SPARC.webhooks.WEBHOOK_URLS", [])
+    def test_no_urls_configured_returns_immediately(self, mock_send):
+        """No-op when no webhook URLs are configured."""
+        notify("job_completed", {"job_id": "test123"})
+
+        mock_send.assert_not_called()
+
+    @patch("SPARC.webhooks._send_with_retry")
+    @patch("SPARC.webhooks.WEBHOOK_URLS", [
+        "https://hooks.slack.com/services/T00/B00/xxx",
+        "https://example.com/generic",
+    ])
+    def test_slack_url_gets_slack_payload(self, mock_send):
+        """Slack URLs receive Slack-formatted payloads, others get generic."""
+        mock_send.return_value = True
+
+        notify("test_event", {"key": "val"})
+
+        # First call (Slack URL) should have "text" key
+        slack_payload = mock_send.call_args_list[0][0][1]
+        assert "text" in slack_payload
+
+        # Second call (generic URL) should have "event" key
+        generic_payload = mock_send.call_args_list[1][0][1]
+        assert "event" in generic_payload
+        assert generic_payload["event"] == "test_event"
+
+
+class TestNotifyJobCompleted:
+    """Tests for notify_job_completed() convenience function."""
+
+    @patch("SPARC.webhooks.notify")
+    def test_sends_correct_event_and_data(self, mock_notify):
+        """Job completion sends proper event type and summary."""
+        notify_job_completed(
+            job_id="batch-001",
+            status="completed",
+            total_companies=10,
+            successful=8,
+            failed=2,
+        )
+
+        mock_notify.assert_called_once()
+        event, data = mock_notify.call_args[0]
+        assert event == "job_completed"
+        assert data["job_id"] == "batch-001"
+        assert data["successful"] == 8
+        assert data["failed"] == 2
+        assert "8/10" in data["summary"]
+
+
+class TestNotifyAlert:
+    """Tests for notify_alert() convenience function."""
+
+    @patch("SPARC.webhooks.notify")
+    def test_sends_correct_event_and_data(self, mock_notify):
+        """Alert notification sends patent_alert event type."""
+        notify_alert(
+            company_name="NVIDIA",
+            alert_type="patent_count_change",
+            message="Patent count increased by 30%",
+        )
+
+        mock_notify.assert_called_once()
+        event, data = mock_notify.call_args[0]
+        assert event == "patent_alert"
+        assert data["company_name"] == "NVIDIA"
+        assert data["alert_type"] == "patent_count_change"
+        assert "30%" in data["message"]